Vol. 27 - Spring 2021

Costly Migration Potential and Foreign Aid Marisa Bianco

SPRING2021

U.S. Economic Policy in Two Crises – 2007/2009 and 2020/?

1Jonas Prager, Ph.D.

Facebook and Electoral Success: Evidence from Germany Ava Vecellio

Myung Ha Kim

Is Citizenship a Derivative of Anti-Blackness?

Kenya Moore

journal of politics

Reinterpreting the Varieties of Capitalism from Germany's Radical Innovation

& international affairs

Volume XXVII

Spring 2021

Journal of Politics & International Affairs Spring 2021 • Volume XXVII New York University

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Spring 2021 • Volume XXVII Journal of Politics & International Affairs New York University

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Spring 2021

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spring 2021 • VOLUME XXVII

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SPRING 2021 • VOLUME XXVII Notes on the Contributors

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U.S. Economic Policy in Two Crises – 2007/2009 and 2020/?

Jonas Prager, Ph.D.

Costly Migration Potential and Foreign Aid Marisa Bianco

Facebook and Electoral Success: Evidence from Germany Ava Vecellio

Reinterpreting the Varities of Capitalism from Germany's Radical Innovation Myung Ha Kim

Is Citizenship a Derivative of Anti-Blackness?

Kenya Moore

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This publication is published by New York University students. The university is not responsible for its contents.

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SPRING 2021 • VOLUME XXVII

STATEMENT OF PURPOSE

EDITOR-IN-CHIEF

The Journal of Politics & International Affairs at New York University is a student-run publication that provides a forum for outstanding student work on relevant, thought-provoking topics in the domestic and international landscape, including research in political science, economics, history, and regional studies.

Emmanuel Hidalgo-Wohlleben

We believe that the student theses published biannually in the Journal—chosen and edited rigorously by our editorial staff—are legitimate and valuable examples of the intellectual growth of politically-minded students and writers at New York University.

DIGITAL MANAGING EDITORS

NOTES Authorization to photocopy items for internal or personal use is granted for libraries. This consent does not extend to other kinds of copying, such as copying for general distribution, for advertising or promotional purposes, for creating new collective works, or for resale. Message sponsored by the NYU Center for Student Life and the College of Arts and Sciences.

Articles published in the Journal of Politics & International Affairs do not represent an agreement of beliefs or methodology, and readers are not expected to concur with all the opinions and research expressed in these pages. Instead, we hope that these pieces are able to inform and inspire dialogue in the NYU community by addressing a wide variety of topics and opinions.

Archival volumes of the journal may be found online at

JPIANYU.ORG Spring 2021

PRINT MANAGING EDITORS Pragya Parthasarathy Roshni Rangwani

Oluwatona Campbell Dylan Liang

ASSOCIATE EDITORS Keerthana Manivasakan Rob Loeser Natasha Roy

EDITORS

Alan Sun Grace Buechler Emily Dai Oviya Adhan Ojas Kharabanda Rishi Dhir Pavel Shirley Sarah Strohecker Anaya Galibdin

SPECIAL THANKS Center for Student Life

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Want to Write for the Journal?

Our editorial staff accepts submissions for consideration throughout the year. To submit your work, or to inquire about being published on our website, email jpia.club@nyu.edu.

Pitch the Print Journal with your original long-form essay or thesis: Works that are published by the print Journal tend to be longer than 5,000 words or 20 pages, double spaced.

Submissions are vetted based on their originality, academic strength, and syntax. Works that are chosen are then polished by several staff editors. The Journal is published every December and May. Submissions from NYU students, as well as non-NYU students, are welcome.

Join JPIA's Digital Team: Our website publishes short blogs that are often around 500 words and feature unique, and creative insights into political issues, current events, and international affairs. We also welcome long-form, reported pieces that are typically 1,000-2,000 words, allowing writers to explore more complex topics with a heavier research component than the blogs. Please reach out to the Editor-in-Chief or the Digital Managing Editors for more information on applying to be a digital staff writer.

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Editor's Note Once a semester, the Journal of Politics & International Affairs publishes outstanding work from student writers across the nation, especially those from New York University.

My tenure as Editor-in-Chief has been quite different from my predecessors.’ Indeed, this is a year I am sure we will all remember for the rest of our lives. This year has produced more sadness, anxiety, and hardship in this country than perhaps any in recent memory. But it has also demonstrated the immense human capacity for solidarity and empathy. These encouraging revelations undoubtedly did little to ease our struggles in the present. Still, if this sentiment can be bottled up and unleashed in the future, I think there is good reason to be optimistic moving forward.

Of course, at the Journal, we have not been immune from adversity, although our burdens indeed are light compared to many others. Nonetheless, how the Team responded to these difficult moments has made me deeply proud of my time in this position and very excited for the Journal’s future.

This semester’s edition features an article by NYU Associate Professor of Economics Jonas Prager, who analyzes U.S. economic policy responses to the Great Recession and Covid Recession. Additionally, in an essay

by NYU alumnus Marisa Bianco, Bianco explains how misconceptions about migration costs influence the amount states spend on foreign aid. We are also excited to present a thesis by NYU Law student, Ava Vecellio, exploring how political parties’ social media presence impacts their electoral vote shares. In another paper, former NYU master’s student Myung Ha Kim compares German and American varieties of capitalism and analyzes the differences between their proclivities for radical innovation. Finally, we are happy to showcase the work of Gallatin master’s student Kenya Moore, who examines the relationship between citizenship and anti-Blackness through the lens of decolonization, socio-historical arcs, and relevant legal doctrines and jurisprudence.

We sincerely hope that you enjoy reading these pieces, and we thank you for your continued support. As always, we encourage you to submit your research papers and theses, and we look forward to reading them.

Take care and be well.

Spring 2021

–– Emmanuel Hidalgo-Wohlleben, Editor-in-Chief

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NOTES ON CONTRIBUTORS JONAS PRAGER, Ph.D.

Jonas Prager, Ph.D., is an Associate Professor of Economics at New York University. Professor Prager obtained his Ph.D. in Economics at Columbia University and is affiliated with the C.V. Starr Center for Applied Economics and the Center for the Study of Central Banks at NYU. His areas of research and interest center on privatization and banking regulation.

MARISA BIANCO

Marisa Bianco graduated from New York University in May 2020, summa cum laude, with degrees in International Relations and Spanish. During her undergraduate career, she worked for the European Foundation of Society and Education in Madrid, Spain, the global political consulting firm Richard Attias & Associates, and the Federal Defenders of New York. In the future, she hopes to combine her interests in global politics with her creative interests and love for writing. Originally from Omaha, Nebraska, she currently lives and works in Córdoba, Spain.

AVA VECELLIO

Ava Vecellio is a 2020 graduate of New York University’s College of Arts and Science, where she graduated summa cum laude, phi beta kappa, with an honors B.A. in International Relations and minors in History and German. The subject of her thesis and much of her professional experience center around the use of social media in our increasingly interconnected political word. She is currently attending the New York University School of Law with a general interest in litigation work.

MYUNG HA KIM

Myung Ha Kim obtained her Bachelor’s degree in International Studies at Bryn Mawr College in 2017 and her Master’s degree in Politics at New York University in 2020. Her M.A. thesis examined how domestic institutions related to economic freedom promote the birth of startups in advanced industrialized countries in the current digital era. Her research interests pertain to global technological leadership, digital transformation and national innovation policies.

KENYA MOORE

Kenya Moore completed her early coursework in Global Affairs, with a concentration in Global Inequalities and Responses, obtaining an IPA in Public Policy and Management, Perspectives, and Issues at SOAS University of London. During her M.A. program at Gallatin, concentrating in Jurispredence and Social Policy, Kenya aims to continue discovering ideas of communal liberation outside of existing social and legal frameworks through her interest in overlapping academic fields and lived experiences, leveraging sociological jurisprudence and socio-historical moments, to explore relations such as that between citizenship and Blackness.

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U.S. Economic Policy in Two Crises – 2007/2009 and 2020/?

Jonas Prager, Ph.D.

The global financial crisis (GFC) of 2007 to 2009 turned out to be a perfect storm. A number of financial market events that individually would have imposed but a small impact on the financial system coalesced in a brief time period to wreak havoc on the US economy and from there on to economies around the world. At the same time, the US real economy suffered from the Great Recession (GR, December 2007 to June 2009), with real output declining by almost 5 percent and the unemployment rate more than doubling from 4.4 percent to 9.5 percent. (The causal interrelationship among the GFC and the GR are beyond the page constraints of this article.)

The world’s financial and economic systems survived if weakly primarily because of timely action taken by the world’s fiscal and monetary authorities. This brief paper focuses on the response of the US policymakers to the GFC and GR to comprehend how the lessons of the past were implemented in the current pandemic.

First, some background. As the US economy thrived during the early 2000s – for example the unemployment rate dropped from 6.2 percent in July 2002 to 4.9 percent in December 2007 -- the stage was ripe for a boom in the housing market. Americans bought and upgraded their housing stock, a normal phenomenon in prosperous times. Thus, between late 2001 and early 2004, housing prices rose at an annual rate of around 5 percent a year. They increased to an annual rate approaching 9 percent between early 2004 and late 2006 as the housing market became an outlet for speculation.

Both banks and so-called shadow banks – unregulated financial institutions including major investment banks like Goldman Sachs and Lehman Brothers – were eager to supply financing. And as a result of a number of financial innovations, these institutions were able to do so without taking on much default risk. Instead, they passed on the risk to others. The investors that bought first the mortgage-based assets and then other types of credit instruments that were packaged by investment bankers perceived that risk to be small. In part they thought they could insure themselves against risk of default and in part because of their confidence in a rising trend of housing prices. At the same time, increasing financial sophistication led to a plethora of new financial instruments that again were perceived as safe; the security rating agencies rated assets worth trillions of dollars as virtually risk-free. Unfortunately, a house of cards was being built in the financial marketplace. It is ironic that many of these shadow banks bought some of the same types of securities they were selling, taking back the default risk that they had initially passed on to others. But no less important, they were highly leveraged, which meant that the banks had borrowed significant proportions of their balance sheets and financed them by continuous, daily renewals. Few thought about the consequences should the flow of short-term lending to these shadow banks be curtailed.

Yes, they had shifted some of the credit risk, but they were exposed to liquidity risk, subjecting themselves to an updated version of a classic bank run.

Unfortunately, the good times came to an end. Housing prices started falling in mid-2006 followed by declines in the values of securities that had been predicated on the belief in ever-rising housing prices. That put pressure on the shadow banks and, of course, on the owners of mortgage-related credit instruments.

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The near failure of Bear Stearns (BS), the smallest of the big 5 US investment banks, in March 2008 drives this point home. During February and March 2008, BS borrowed daily sums of between $15 and 21 billion. But as its lenders began to lose confidence in Bear Stearns’s ability to repay its loans in light of the downturn in financial asset values, they drastically curtailed lending. On March 11 and 12 BS was able to borrow around $12 billion; the next day, it could obtain no more than $2 billion. Bear Stearns imploded. If not for assistance from the Federal Reserve that enabled BS to be sold to JP Morgan Chase (JPMC), there would be no more BS (it is now a subsidiary of JPMC).

Essentially the same story repeated itself in September 2008, this time with Lehman Brothers, another of the now big 4 independent investment banks. As Lehman piled up losses, its lenders held back so much so that Lehman was forced to declare bankruptcy on September 15, 2008. The consequences of the unforeseen failure including the refusal of the Treasury and the Federal Reserve to provide backup loans shocked the financial markets. The stock market plummeted immediately, losing 4.4 percent in just one day, runs began on money market mutual funds – shadow-bank deposit-like institutions that held substantial amounts of short-term debt – and the American Insurance Group, a gigantic multinational financial conglomerate that could not find free-market funding for its liquidity needs, was on the verge of collapse (the value of a share of AIG common stock plummeted from over $1400 in June 2007 to $31.20 at the end of 2008).

The paralysis in the financial marketplace led to a breakdown in the short-term funding of many globally prominent firms, foreshadowing their potential collapse. As a US Treasury official pithily commented about the week of September 15, 2008: “At this point, the banking system stops functioning.

You’re pulling four trillion dollars out of the private sector … and giving it to the government in the form of T-bills [viz. government securities in a “flight to safety”]. That was commercial paper [unsecured shortterm securities] funding GE, Citigroup, FedEx, all the commercial-paper issuers. This was systemic risk.

Suddenly, you have a global bank holiday.”1

Actions taken both by the Federal Reserve and the US government preserved the financial system and prevented the US economy from collapsing. On the fiscal side, the landmark event was the Economic Stimulus Act of (February) 2008 that provided funds directly to low-income residents, incentives for business investment, and homeowner relief at an estimated cost of $152 billion. It was followed a year later, at the tail end of the GR, by a substantially larger (estimated cost to the US government of $787 billion) American Recovery and Reinvestment Act that also provided tax relief to businesses and consumers as well subsidies to the unemployed and low-income workers. These fiscal actions were typical countercyclical measures: when the economy is weak, stimulation is called for.

The Fed, too, used its countercyclical tools, specifically interest rate policy to help stabilize the real economy. Thus, the Federal funds rate, a key interest rate-indicator, was pushed down from 6.25 percent in August 2007 to 4.25 percent by December2007 to 2.25 percent after the Bear Stearns collapse 1 Quoted in James B. Stewart, “Eight Days,” The New Yorker, September 21, 2009. You might want to

watch “Too Big to Fail,” a DVD that does an excellent job in conveying the panic of late 2008.

If these summary paragraphs leave you somewhat confused, you might also want to read my article, “The Financial Crisis of 2007/8: Misaligned Incentives, Bank Mismanagement, and Troubling Policy Implications,” (Economics, Management, and Financial Markets, July 2013).

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JONAS PRAGER, Ph.D.

in March 2008 and to 0.25 percent in December 2008, an historically low rate. But note that economists have long differed as to monetary policy’s impact in countering a recession. Most feel that lower interest rates can encourage business and certain types of consumer expenditures but cannot compel such spending.

Monetary policy is decidedly a supporting actor to the star of anti-recession fiscal policy.

In sharp contrast, the Federal Reserve and the US Treasury turned entrepreneurial when it came to countering panic in the financial marketplace. Their actions were both substantive and psychologically oriented, aiming to calm the fears of market participants. The Fed and Treasury policymakers implemented a whole array of new instruments to fund and calm the financial system. While too numerous to detail here, they ranged from expanding the ability of market participants to borrow from the Fed to lending significant funds to AIG to providing federal guarantees to holders of money market fund deposits. And let us not forget the Troubled Assets Relief Program created in October 2008 by the Emergency Economic Stabilization Act that not only enabled funding of financial institutions in trouble but also provided a lifeline to General Motors and Chrysler.

How impactful were all these interventions? Well, neither the financial system nor the economy collapsed, although recovery did take some time. But what is clear is that all these policy initiatives were reactive, seat-of-the-pants responses to shockingly unexpected market events.

To turn now to the economic effects and policy measures taken during the pandemic – and of this writing, while the pandemic is not yet over, the worse appears to have been left behind – we again turn to some fundamental data.

But first as a background comment, let’s begin with an astute remark by Michael Corbat, Citigroup’s CEO: “This [pandemic] isn’t a financial crisis…. It’s a public health crisis with severe economic ramifications.” (The New York Times, April 15, 2020) In other words, we’re not reliving the causes of the GFC or the GR, but the economic consequences are quite similar. It is to the economic and financial disruptions that the fiscal, monetary, and financial stability policymakers must respond.

In terms of the health situation, a rapid escalation in US Covid-19 cases and related deaths started in March 2020. The number of US cases rose from a statistically insignificant number in midMarch to over 1 million in mid-May. The Covid-19 death rate followed a similar pattern: from virtually none in late-March to around 100,000 by late May. By late September, the death rate doubled and doubled again by January 2021. The death rate from Covid-19 shockingly topped 500,000 by the end of February 2021.

The policy response on the health and wellness side was to shut down broad swaths of the US economy. By late March, 20 states had drastically limited nonessential public and private activities, which hit hard on many sectors of the economy. Service sectors -- leisure and hospitality and its related subsectors including transportation, energy, and tourism and in-store sales and some related manufacturing industries -- bore the brunt of the decline. Two key data points drive the economic devastation home. First, in the second quarter of 2020, GDP fell by over 9 percent, a decline that is unique in magnitude since 1947, the first year that official US records are available. Second, the unemployment rate skyrocketed from 3.5 percent in February 2020, the accepted beginning of the downturn, to 14.3 percent in April 2020. (Take a look at a chart of the unemployment rate from 1948 to April 2020; you will see nothing comparable to the explosive uptick between February and April.)

The US policy responses were noteworthy. First, the actions were taken emphatically and quickly.

On the fiscal front, between March and April, Congress allocated not-quite $3 trillion in various types of

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economic aid. In sharp contrast to the Great Recession, where the ratio of fiscal stimulus to GDP was 6.5 percent, by the fourth quarter of 2020, the ratio almost doubled to 12.6 percent. In terms of timing, whereas the 2008/2009 recession saw two fiscal actions, one near the beginning and one near the end, the pandemic response was 5 stimulus actions in just 2 months. And note that the fiscal response continues with the recently-passed $1.9 trillion “American Rescue Plan” with goodies for many, and a $2 trillion “American Jobs Plan.” Spending is aimed at infrastructure improvement as well as a hodge-podge of stimulus and taxing provisions that awaits Congressional action as of this writing.

The story is equally positive in terms of Federal Reserve actions, with decisive and speedy actions.

On the monetary policy front, the Federal funds rate was a low 1.6 percent at the beginning of March. It was reduced to zero by the end of the month, where it remains (and will remain for the foreseeable future).

At the same time the Federal Reserve System purchased sizeable volumes of securities on the open market, a typical monetary measure to expand the money supply and lending opportunities.

The Fed’s financial stability-related actions were similarly implemented swiftly. A slew of liquidity facilities was immediately offered to a broad range of market players, providing backup borrowing options should the financial markets freeze as they did in October 2008. In early April 2020, the Fed broke new paths, providing credit to medium-sized businesses and to municipal governments. The fact that financial markets did not collapse may legitimately be attributed to this series of preventive measures by the Federal Reserve System. And the strong recovery in 2021 – GDP rose by an estimated whopping 6.4 percent in the first quarter -- while leaving the economy well below capacity, can also be attributed to the strong and swift public policy measures.

Of course, while we may glimpse the light at the end of the tunnel, the US economy is still in the tunnel. Some economic sectors remain weak. And just as not all segments of the labor force were affected equally -- lower-income workers who are part of the service economy have suffered more of an income drop than employees who can work from home, not needing direct contact with their customers — so has the fledgling recovery been better for some than for others. Moreover, and not surprisingly, implementation problems have surfaced as has significant fraud. And while differences in policy-approaches between political parties have been muted in much supportive legislation, currently the chasm between Congressional parties needs to be bridged to move forward.

To summarize: The fiscal and monetary policymakers did absorb the lessons of the GFC and the GR. They strongly and swiftly worked to counteract the economic and financial consequences of the current pandemic. But it’s premature to measure the policies’ effectiveness especially as we’re still suffering from the pandemic. Economists will be evaluating their impact in the years to come. Stay tuned.

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Costly Migration Potential and Foriegn Aid Marisa Bianco

This paper seeks to determine how perceptions of costly migration potential influence incumbent governments’ decisions on how to allocate Official Development Assistance (ODA). I borrow a new and unique measure of costly migration potential developed by Leblang, Schneider, and Tobin (2019), and tests its effect on a bilateral foreign aid dataset of all 29 OECD donor countries to 153 recipient countries from 1970-2015. I find that costly migration potential has a positive and significant effect on foreign aid. The results support the theory that incumbent governments use foreign aid as a tool to reduce potentially politically harmful migration.

Introduction

It is no coincidence that the largest donor-countries of foreign aid are also key destinations for migrants from the developing world. We have also seen that migration can be costly for destination countries and their governments, which has led to a rise of anti-immigrant parties and candidates. While nationalist parties and candidates in OECD countries differ in their immigration preferences, polls reflect a clear rise in anti-immigrant sentiments.1 This paper asks: do donor countries give more foreign aid to countries from which they perceive a threat of costly migration? Addressing the root causes of migration through foreign aid has consistently been a relevant part of policy conversations. For example, the European Commission argued in a 2008 communication that the European Community should adopt “a view to strengthening EU efforts to address the root causes of migration.”2 In 2010, Former Deputy Prime Minister of Britain Nick Chegg said, “if you want to stop people upping sticks and moving across continents and coming to settle in Europe and here, you have got to make sure the circumstances are better for them.”3 In a 2019 interview with NPR, Shannon O’Neil of the Council on Foreign Relations mentions that the U.S. Congress has sent around $750 million a year to Central America “to try to deal with these root causes [of migration].”4 While multiple papers investigate whether foreign aid reduces migration, Clemens and Postel (2017) point out that beyond the above anecdotal evidence, there is still little research on whether donor countries actually send more aid to migrant-sending countries in an attempt to address the root causes of migration.

This paper’s main objective is to prove that the potential for politically-costly migration influences foreign aid donor countries’ willingness to allocate aid. More specifically, governments that see 1 https://www.bbc.com/news/world-europe-36130006 2 COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT, THE COUNCIL, THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONS - https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2008:0611:FIN:EN:PDF 3 https://www.standard.co.uk/newsheadlines/clegg-to-push-aid-goal-at-un-summit-6515846.html 4 https://www.npr.org/2019/03/06/700873481/the-root-causes-of-migration-in-central-american-countries

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a potential for political repercussions from migration pressures are more likely to give foreign aid to the countries behind the migration pressures. I determine the effect of costly migration potential on foreign aid, building on Leblang, Schneider, and Tobin’s research, “Protecting Home Abroad: Financial Rescue as Migration Prevention” (2019) and Bermeo and Leblang’s “Migration and Foreign Aid” (2015). Bermeo and Leblang find a strong, positive relationship between existing migrant populations and aid allocation.

I investigate whether this relationship still holds when using Leblang, Schneider, and Tobin’s measure of costly migration potential. I also add to Bermeo and Leblang by comparing the effect of costly migration potential on bilateral and multilateral official development assistance in a placebo test. If costly migration potential is truly a determinant of aid allocations, we would expect that the effect would be stronger on bilateral ODA.

My results provide further support for Leblang, Schneider, and Tobin’s argument that incumbent government’s expectations of costly migration motivate them to use foreign policy as an attempt to lessen that migration. They find a positive effect of potential political backlash from migration on the likelihood that a migrant-receiving country will provide a migrant-sending country a bilateral bailout during a credit crisis in the sending country. I borrow their measure of costly migration potential and find that it has an effect not only during credit crises, but also on the use of Official Development Assistance (ODA) in general. While it is uncertain whether foreign aid reduces migration, this paper shows that government perceptions of costly migration potential encourage the use of foreign aid as a tool to reduce migration costs.

Literature Review Determinants of Foreign Aid

Countries do not allocate aid solely based on altruism. Foreign aid literature shows that distributing aid to developing countries is not a selfless decision process where donors objectively evaluate the need of each receiving country. The choice of how and where to spend foreign aid money is dictated by a variety of factors, such as economic and cultural ties with donors. Foreign aid is often distributed “eclectically” so that “developing countries with greater political, historical and cultural affinities with donors, as well as countries with greater economic and geo-strategic importance, receive more aid than other countries with similar — or greater — levels of need” (Vázquez and Sobrao 2016: 3). Furthermore, donor countries use foreign aid as a tool to solve domestic problems. Hjertholm and White (2000) argue about the fact that bilateral aid still exists despite evidence that multilateral aid may be more effective shows that donor countries’ individual preferences play a significant role in their aid decisions. Those individual preferences are driven by incumbents’ desire for political survival. This paper aims to determine how large of a role expected costly migration plays in donors’ aid decisions.

Many scholars have analyzed which factors specific to the target country have the greatest effect on aid allocations. The main relevant factor is recipient need, which can be measured by income, life expectancy, literacy rates, and employment rates, among many others. Hoeffler and Outram (2011) and Kim and Oh (2012) both study the effect of recipient income per capita on aid allocations. Ji and Lim (2018) find that recipient needs, such as undernourishment and food inadequacy, influence the allocation of agricultural aid. Interestingly, Hoeffler and Outram (2011) find that recipient merit, or whether the recipient country has good democratic institutions, low corruption, etc., has very little effect on donor

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MARISA BIANCO

countries’ aid allocation decisions.

My independent variable, borrowed from Leblang, Schneider, and Tobin (2019), most closely follows the literature studying the effect of factors shared by the dyad, or the pair of donor and receiving countries. An example of a dyad characteristic is the trade relationship between donor and receiving country. Hoeffler and Outram (2011) study the effect of the flow of import and exports between donor and recipient. They also study the effect of whether the two countries have similar geopolitical preferences, using commonalities in United Nations voting behavior. They find that the major aid donors give more aid to countries they trade with and countries who vote similarly to them in the UN. Similarly, Dreher et. al. (2018) show that U.S. allies receive more foreign aid when said allies vote in concordance with the U.S. on the United Nations Security Council. These findings emphasize the role of donor self-interest in aid allocation. This paper analyzes the effect of another dyad characteristic — costly migration potential — that also reflects donor self-interest, controlling for the dyad-level variables studied by Hoeffler and Outram (2011). I add to the scholarship on how foreign aid is influenced by donor government’s motivation to help themselves politically — using aid to solve problems within the donor country.

Determinants of Migration

There are various theories and methods postulating the main determinants of migration. The migration literature tends to focus on push and pull factors of migration. Push factors are factors relating to the migrant’s home country. Some examples include high unemployment, natural disasters, religious or ethnic discrimination, violence, and poor healthcare. Pull factors, on the other hand, are factors relating to the migrant destination country. Examples include better security, more job opportunities, better medical care, and more political or religious freedoms.5 Ortega and Peri (2013) use a microeconomic model to find a strong link between destination country income per capita and international migration flows. According to their analysis, a 10% increase in income-per-capita in the destination country is accompanied by a 7.6% increase in migrant flows. This paper focuses on how foreign aid can be used by migrant-destination countries to improve conditions in migrant-origin countries and therefore decrease push factors of migration.

Lastly, it is relevant to note that migrant-receiving countries develop migrant communities as migration occurs. Massey et. al. (1993) emphasize the role of migrant networks, or “sets of interpersonal ties that connect migrants, former migrants, and non-migrants in origin and destination areas through ties of kinship, friendship, and shared community origin” (448). They argue that these networks decrease the costs of migration. The model I use takes migrant stocks into account when measuring migration potential, reflecting Massey et. al.’s argument.

Migration and Foreign Aid

While explanations for the link between migration and foreign aid allocation have been extensively researched, scholarship exploring this link has thus far focused on a different, but related question to the one I am asking: do foreign aid disbursements affect migration? Some scholars have found evidence of a positive relationship. For example, Belloc (2015) finds that development assistance has a positive and 5 Krishnakumar, P., and T. Indumathi. 2014. “Pull and Push Factors of Migration.” Global Management Review 8 (4): 8–13.

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significant effect on migration outflows in Sub-Saharan Africa. Berthélemy, Beuran, and Maurel (2009) estimate a threshold income per capita that determines whether an increase in aid will lead to migration.

At income levels below the threshold, migration will increase since aid will enable more people to afford the costs of migrating. At income levels above the threshold, increased aid will reduce migration. On the other hand, Lanati and Thiele (2019) find evidence of a positive relationship — that foreign aid is effective in reducing migration. Lanati and Thiele (2019) argue their results are more reliable than Berthélemy, Beuran, and Maurel (2009) because they use migrant flow data. Berthélemy, Beuran, and Maurel, on the other hand, use migrant stock data to proxy for migrant flow, which may be biased. Their cross-section time-series data also allows them to control for donor and recipient country fixed effects, which accounts for the fact that migrants are not only comparing conditions between their home country and a foreign aid donor country, but all other possible destination countries. However, the bulk of these papers’ analyses focus on how aid allocations cause migration. This paper studies the other causal direction by explaining aid motivations rather than aid effectiveness. I attempt to isolate migration, specifically the potential for costly migration, to determine its effect on foreign aid allocation.

A few papers empirically evaluate migration flows as a causal element of foreign aid. In one of the first papers examining this relationship, Lahiri and Raimondos-Møller (2000) develop a model of foreign aid allocations based on the lobbying efforts of ethnic groups in the donor country. Through political contributions, immigrant groups can influence donor governments to allocate more aid to their respective home countries. The model predicts that a larger migrant population from a particular country living in the donor country causes greater aid disbursements from the donor country to that country. My independent variable of costly migration potential takes into account migration stock populations in donor countries. A larger stock increases migration potential. This occurs through the creation of networks, which makes it easier for new migrants to come, and lobbying. The two mechanisms are not mutually exclusive.

Czaika and Mayer (2011) examine how forced migration affects aid allocation. They distinguish between three types of forced migrants: those who have been internally displaced, refugees in bordering countries, and those seeking asylum in OECD countries. They find that cross-border displacements have a greater effect on aid than internal displacements. In addition, they analyze differences in short-term emergency aid and long-term development aid. They find that donor countries are much more likely to give development aid to countries sending asylum seekers. Bermeo and Leblang (2015) expand on Czaika’s findings by analyzing migration as a whole and its effects of foreign aid, rather than just forced migration.

They find support for two hypotheses: donors direct aid to migrant-sending countries in order to reduce migration, and migrants living in the donor country lobby in favor of more aid to their home country. They find that “a 10 percent increase in the size of the migrant population from a particular recipient residing in a donor country increases aid commitments to that recipient by nearly 7 percent” (Bermeo and Leblang 2015: 461).

Bermeo and Leblang use migrant stock data to prove a causal link between migration and foreign aid. Vázquez and Sobrao (2016) go further by presenting a model that illustrates a two-step mechanism through which governments allocate aid. Their model attempts to explain how increases in migration flows to donor countries alter the geographical allocation of foreign aid. They test their model on whether immigration priorities affected aid disbursement in Spain prior to the economic crisis in 2009, when Spain’s foreign aid budget drastically decreased. They find that the probability of a country receiving Spanish aid

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increases 18% with every 1% increase of the immigrant population from that country. This paper follows in Vázquez and Sobrao’s footsteps by focusing on how foreign aid decisions are made and how large of a role migration plays in those decisions.

The literature examining the link between migration and foreign aid concurs that migration affects foreign aid allocations. Both Bermeo and Leblang, and Vázquez and Sobrao, find a strong, positive relationship between existing migrant populations in a donor country and aid allocations from that country.

The main problem in the literature is that thus far, migration is measured by past flows or stocks, when we know intuitively that expectations of future migration also play a role. Governments don’t make decisions about where to send aid based solely on migration that has already occurred. The link between migration and foreign aid needs to be tested using an independent variable that accounts for a country’s perceived threat of potential migration. Migration from some countries, especially those with greater cultural distance, is more politically costly for incumbent governments than migration from other countries, or those culturally closer to the migrant-receiving country. We need an independent variable that reflects these differences in political costs, yet none of the literature takes into account potential migration and its costs. This paper therefore investigates a new question: whether costly migration potential, as perceived by the donor country, affects aid allocations. I examine whether the finding that migration concerns factor into foreign aid donors’ decisions still holds when using costly migration potential as the independent variable.

Theory and Hypothesis

This paper theorizes that the expectation of costly migration induces migrant-receiving countries to allocate foreign aid to migrant-sending countries. This is based on the assumption that incumbent governments want to be reelected. In situations of term limits, incumbent governments prefer to have someone from their party replace them.6 Migration affects the political futures of incumbent governments.

This is demonstrated by Bernhard and Leblang’s (2016) analysis of the role of potentially-costly migration from Greece in Germany’s decision to provide a second bailout. They argue that the potential migration could have cost Merkel her chancellorship, which is why she supported a bailout. Overall, a larger-thanexpected inflow of refugees negatively affects incumbents’ time in office throughout OECD countries (Bernhard, Leblang, and Post 2017).

Why do migration costs harm incumbent governments? There is ample literature on attitudes toward migration (see Citrin, Green, Muste, and Wong’s comprehensive 1997 paper). Various studies show how increases in migrant flow are associated with more negative attitudes toward migration. One key finding is the importance of the race and culture of said immigrants. For example, Eger (2010) shows how ethnic heterogeneity from immigration decreases support for welfare spending in Sweden. Notably, Bridges and Mateut (2014) find that whether economic or non-economic factors shape attitudes towards immigrants depends on the ethnicity of the immigrants. This theoretical background explains why the independent variable in this paper is weighted by genetic distance — in order to capture the social tensions that arise from ethnic heterogeneity. Furthermore, Borjas (2003) finds that immigration lowers wages for competing workers, and Hanson et. al. (2005) find that “high exposure to immigration fiscal pressures” is associated 6 Note that all of the migrant-destination countries included in my analysis are OECD countries, and therefore all operate under a democratic electoral system.

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with reduced support for open immigration policies. Even a small effect on wages or unemployment can have significant political repercussions for the incumbent government.

These political costs of migration incentivize incumbent governments to use tools at their disposal to attempt to reduce migration. ODA is one of those tools. The most recent evidence from Latani and Thiele (2019) shows that foreign aid reduces migration flows. This paper follows their theory, which argues that aid allows for improved public services, which reduces push factors of migration. Foreign aid therefore has the potential to reduce migration and the political costs associated with it. The investment in foreign aid has political returns for incumbent governments.

If governments believe that foreign aid reduces costly migration, they should be incentivized, ceteris paribus, to provide more foreign aid to countries from which they perceive a higher costly migration potential. This leads to the following hypothesis: HA: Donor countries give relatively more aid to countries from which they perceive a costly migration potential.

This theory does not assume that foreign aid will consistently reduce costly migration. In the face of uncertainty, governments must use their expectations to make decisions. ODA is one tool governments can use to prevent migration. Even if foreign aid is unsuccessful in reducing migration, there are still political benefits. The incumbent’s decision to increase aid signals to their audience that they are doing something to address the problem, which can increase their political popularity. McLean and Whang (2014), for example, assert that the use of economic sanctions, another foreign policy tool, is a way for politicians to demonstrate their competence when voters expect a response to a foreign policy crisis.

Research Design and Data

I argue that the costly migration potential from a migrant-sending country makes a migrantreceiving country more likely to provide foreign aid to that country. This paper uses a full panel, comprising of multiple migrant origin and destination countries across a wide number of years. Such extensive data allows me to better control for factors specific to origin or destination countries. I constructed a data set that includes foreign aid commitments from the OECD and estimated migration potential from Leblang, Schneider, and Tobin (2019) for country pairs from 1970-2015. The unit of analysis is the migrant-sending country and migrant-receiving country dyad in a particular year. The variation in costly migration potential comes from the differences between countries. A migrant-receiving country will perceive a higher costly migration potential from a migrant-sending country to which it is more similar (i.e. they have a shared colonial heritage, shared language, and there is a large migrant stock of people from the sending country already living in the receiving country).

Dependent Variable

For the dependent variable, I use dyadic data on foreign aid commitments from the OECD database. Data are reported in constant 2017 dollars. I use the log of aid commitments in my analysis. The data includes bilateral foreign aid from all 29 OECD donors to 153 recipients from 1970-2015. I also test my hypothesis using a subset of the data, beginning in 1990, because Bearce and Tirone (2010), among others, argued that the nature of foreign aid changed after the end of the Cold War. Prior to 1990, Cold War strategy played a much more significant role in how donor countries distributed aid. I also run my model using an alternative dependent variable, aid disbursements, as a robustness test. Data are from the

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OECD. Aid commitments and aid disbursements are strongly correlated, with a correlation coefficient of 0.81.

Independent Variable

I borrow Leblang, Schneider, and Tobin’s measure of migration potential as my treatment variable. Migrant flows are estimated using the below gravity model. In the equation, population is positively related to migrant flows, and distance is negatively related. The equation also includes a dummy variable for whether countries o and d share a border, have a common language, or share a colonial heritage. These factors affect the costs that migrants face when moving to a new country. For example, it is less costly to move to a country where most native citizens speak your language. Because there is little exogenous variation, they interact year dummy variables with distance. They define the Migration Potential variable by the upper bound of the 95% confidence interval of the below regression.7

Leblang, Schneider, and Tobin describe their model with the following:

“Mijt denotes migrant flows from country i into country j at time t, population refers to the log of

population in country i or country j at time t, distance is the log of the great circle distance between i and j, and border, language, and colony are all dummy variables coded as 1 if the countries share a common border, common official language, or common colonial heritage, and 0 otherwise. MigStock measures the accumulated stock of migrants (the foreign-born population) from country i residing in country j at time t. Finally, γ denotes a set of dummy variables for all origin and destination countries.

We obtain the data for migrant flows and stocks from Fitzgerald, Leblang, and Teets (2012). Data on population are from the World Bank’s World Development Indicators. Finally, data on distance and commonalities are from the CEPII database.”

However, this measure of migration potential does not account for the potential political costs of migration as perceived by incumbents. As described in the above theory section, these costs stem from racial, ethnic, and/or cultural differences between the migrant-sending and migrant-receiving countries.

To reflect costs, I weigh the Migration Potential variable by genetic distance, using the same weights as Leblang, Schneider, and Tobin. The weights come from Spolaore and Wacziarg (2015), who developed measures of genetic distance by analyzing blood samples from different ethnic groups. Their measures are highly correlated with differences in language and religion between countries. In my research design, these genetic weights serve to represent the potential for social conflict from the influx of migrants from a different culture than the native population.

Controls 7 Country i signifies country o (for migrant origin) in my dataset. Country j signifies country d in my dataset (for migrant destination).

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My project faces a significant identification problem because there is little exogenous variation in migration potential. I employ a variety of control variables to overcome this problem and make my estimates as close to causal as possible. My main control variables are individual country, year, and countrydyad effects. Fixed effects are employed as controls to remove as much omitted variable bias as possible.

Country fixed effects rule out time-invariant country-level differences. Year fixed effects rule out timevariant trends that do not vary across dyads. Country-dyad fixed effects rule out time-invariant dyad-level differences. I expect the fixed effects to rule out many omitted variables, such as the distance between the two countries and whether the dyad shares a colonial heritage or a common language.

There are a few additional variables I control for. These variables vary across dyads and across time, and therefore are not controlled with fixed effects. I control for variables that may help determine whether a country receives foreign aid from a particular OECD country. First, I control for a variety of variables that represent the geopolitical importance of the migrant origin country to the migrant destination country. I use two control variables to represent geopolitical importance. First, I control for whether the two countries share a regime type. OECD countries may give more aid to non-democracies, believing that economic development could lead to democracy. I constructed a dyadic dataset of regime type and created a dummy variable representing whether the two countries have the same regime type (democracy or non-democracy). Data are from Boix, Miller, and Rosato (2013). Second, I control for similarity in foreign policy preferences between the dyad, using UN General Assembly ideal points. I constructed a dyadic dataset of UN ideal points and created a variable representing the absolute value of the distance between ideal points (between the OECD country and the developing country). Data are from Voeten, Strezhnev, and Bailey (2009). Lastly, I control for the economic relationship between the dyad, because migrant destination countries may be more inclined to give aid to countries that they trade with.

This was demonstrated by Hoeffler and Outram (2011). To proxy for economic relationships, I control for smoothed total trade flows between the dyad each year. Data are from the Correlates of War Project, Version 4.0.

The summary statistics for the variables used in this paper are presented below. Note that the variables are measured at the dyad-year level.

Table 1: Summary Statistics

Variable

Mean

Standard Deviation

Min

Max

Number of Observations

Source

173,416

Leblang, Schneider, and Tobin (2019)

Independent Variables Migration potential, dyadic

1,034

8,113

1.04

978,900

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Interpolated Migration Stock Values (number of people)

10,100

134,000

0

1.21 • 107

174,167

Leblang, Schneider, and Tobin (2019)

Weights for Independent Variable Weighted genetic distance, dyadic

0.0344

0.0167

0

0.0715

151,294

Spolaore and Wacziarg (2015)

Weighted genetic distance (1500), dyadic8

0.0420

0.0199

0

0.0976

151,156

Spolaore and Wacziarg (2015)

Dependent Variables Aid Commitments (millions, constant 2017 dollars)

29.7

161.5

0

20,930

80,518

OECD

Aid Disbursements (millions, constant 2017 dollars)

23.156

113.5

0

13,864

85,995

OECD

Controls Smoothed Total Trade Values

590.4

7002

0

655,800

178,085

Correlates of War Project

Shared Regime Type

0.3978

0.4894

0

1

156,561

Boix, Miller, and Rosato (2013)

Difference between UN Ideal Points

1.626

0.7418

2.98 • 10­-7

5.25

178,255

Voeten, Strezhnev, and Bailey (2009)

Estimation Procedures

I run a time-series cross section regression on the effect of costly migration potential on panel

8 When I run the full model, the control variables are lagged once to avoid posttreatment bias and the dependent variable is lagged twice to account for time trends.

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data of foreign aid allocations of each donor-recipient country pair from 1970-2015. I perform an ordinary least squares estimation with time using a two-way fixed effect model. I anticipated a temporal dependence problem in my analysis. That is, the probability of an intervention (in this case, foreign aid), may be dependent on such interventions in previous years. ODA from country d to country o in time t+1 may be at least in part determined by the ODA from country d to country o in time t. Therefore, the model is run using a lagged version of the dependent variable to rule out this possibility. The following model estimates aid commitments from migrant destination country d to migrant origin country o in year t (and t+1): Aid(odt) = α(odt) + γ(od) + δ(o) + φ(t) + θaid(odt-1) + β(costly migration potential(odt)) + (controls(odt)) κ + ε(odt)

Aid(odt) denotes the predicted dollar value of aid commitments from migrant origin country o to migrant destination country d in time t. γ(od) are dyad-level fixed effects, δt are year-level fixed effects, and φo are migrant origin country fixed effects. aidodt-1 is a one period time lag of the dependent variable, used as a control to rule out country-specific time trends of aid. Costly migration potential is my independent variable of interest, which is constructed by weighting the migration potential variable provided by Leblang, Schneider, and Tobin. Lastly, I include a vector of control variables, mentioned above, that are not ruled out by fixed effects.9 I utilize multi-way country-dyad and year standard error clustering following Cameron, Gelbach, and Miller (2011). Such clustering makes my estimates very conservative.

The costly migration potential variable used in my model is standardized, and foreign aid commitments are logged. Therefore, the estimated beta coefficient means that for a given country, as Migration Potential(weighted) varies across time by one standard deviation, aid increases/decreases by (βx100) percent. With my fixed effects and additional controls, this estimate will be as close to a causal estimate as possible.

Results

I found a positive relationship between costly migration potential and foreign aid commitments.

Results from OLS regressions with standard errors clustered by country-dyad year are presented in Table 2-6. Overall, my results align closely with the theoretical arguments above. Table 2 below includes results using logged aid commitments as a dependent variable from 1970-2015. The coefficient for migration potential (weighted) when using the model with both fixed effects and controls is positive and significant to the 10% level. According to this result, a one standard deviation increase in migration potential (weighted) causes an estimated increase in aid commitments of 4%, all else equal. The results reveal some interesting complexities in the relationship between costly migration potential and foreign aid. Adding the weights to the models with controls and fixed effects increases both the size of the coefficient and its significance level. This is consistent with the theory that perceived potential migration from ethnically and/or culturally different countries results in increased aid allocations.

9 See note 8.

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Table 2: Regression Estimates with Logged Aid Commitments as Dependent Variable, 1970-2015

(1) unweighted

(2) weighted

(3) weighted, 1500

(4) unweighted

(5) weighted

(6) weighted, 1500

Migration Potential (standardized)

0.0403*** (0.0148)

0.0387** (0.0187)

0.0490** (0.0199)

0.0413** (0.00985)

0.0399* (0.0205)

0.0504** (0.0219)

Smooth total trade (logged)

0.109*** (0.0169)

0.107*** (0.0180)

0.0997*** (0.0156)

0.107*** (0.0198)

0.104*** (0.0432)

0.0976*** (0.0191)

Shared regime type

-0.0395 (0.0331)

-0.0411 (0.0341)

-0.0337 (0.0331)

-0.0415 (0.0418)

-0.0435 (0.0432)

-0.0344 (0.0191)

Difference in UN ideal points

0.0105 (0.0333)

0.0348 (0.0326)

0.0453 (0.0320)

0.0142 (0.0383)

0.0392 (0.0379)

0.0491 (0.0372)

Fixed Effects

No

No

No

Yes

Yes

Yes

Controls

Yes

Yes

Yes

Yes

Yes

Yes

Lagged DV

Yes

Yes

Yes

Yes

Yes

Yes

R-squared

0.704

0.679

0.690

0.706

0.682

0.692

N

46,876

42,372

42,124

46,876

42,372

42,124

Standard errors in parentheses * p<0.1, ** p<0.05, *** p<0.01 Controls are lagged once and DV is lagged twice Table 2: Results of OLS regressions showing the relationship between Migration Potential and logged aid commitments. The columns indicate whether Migration Potential was weighted in the model. The red columns include controls and no fixed effects. The yellow columns include both controls and fixed effects.

I employ a variety of robustness tests to confirm, as much as possible, that the relationship between costly migration potential and foreign aid is indeed causal, as the above estimates suggest. First, I used a different set of weights, the genetic distance in 1500, as a robustness test. Data are also from Spolaore and Wacziarg (2015). Leblang, Schneider, and Tobin (2019) use this data to test whether the genetic distance weight is endogenous or simultaneously determined. My results are robust using the genetic distance 1500 weights. I therefore rule out this particular endogeneity concern. Interestingly, Leblang, Schneider, and Tobin do not find a significant effect of migration potential using the 1500 weights on bilateral bailouts.

I find that migration potential coefficients are positive and significant on ODA with both the new genetic distance weights and the genetic distance 1500 weights.

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Next, I test my model using only observations from 1990-present, rather than 1970, to examine whether there exists a possible change in foreign aid motivations after the fall of the Soviet Union. Results can be found in the Appendix, Table 1A. Interestingly, the coefficients on migration potential are larger in magnitude when using this subset of observations. I estimate a 6% increase in aid commitments from a one standard deviation increase in migration potential (weighted), all else equal. This is more than triple the effect using the same model on data beginning in 1970. These findings provide support for the hypothesis that the effect of migration concerns on foreign aid grew in importance after the end of the Cold War. To further confirm this hypothesis, I generated a dummy variable that takes the value of 1 when an observation occurred after 1990. I then ran my regression using an interaction term interacting the dummy variable with migration potential. The interaction term was positive and significant to the 10% level. This means that the effect of migration potential on aid commitments increases for observations after 1990.10

Further Robustness Tests: Alternative Dependent and Independent Variables

As mentioned in the above data section, I run the same regressions using an alternative dependent variable: aid disbursements. I use both a lagged and logged version of this variable as well. The results are robust to using aid disbursements. All else equal, the predicted change in aid disbursements from a one standard deviation increase in costly migration potential is around 2.5-3%, depending on the model used.

Table 3: Regression Estimates with Logged Aid Disbursements as Dependent Variable, 19702017

(1) unweighted

(2) weighted

(3) weighted, 1500

(4) unweighted

(5) weighted

(6) weighted, 1500

Migration Potential

0.0262** (0.0121)

0.0247* (0.150)

0.0339** (0.0168)

0.0268** (0.0133)

0.0254 (0.0164)

0.0347* (0.0187)

Smooth total trade (logged)

0.0943*** (0.0132)

0.0903*** (0.0130)

0.0899*** (0.0122)

0.0935*** (0.0175)

0.0891*** (0.0183)

0.0889*** (0.0172)

Shared regime type

-0.0258 (0.0270)

-0.0250 (0.0295)

-0.0248 (0.0274)

-0.0266 (0.0332)

-0.0256 (0.0347)

-0.0241 (0.0328)

Difference in UN ideal points

-0.00478 (0.0297)

0.0178 (0.0260)

0.0236 (0.0253)

-0.00270 (0.0401)

0.0208 (0.0357)

0.0257 (0.0349)

Fixed Effects

No

No

No

Yes

Yes

Yes

Controls

Yes

Yes

Yes

Yes

Yes

Yes

Lagged DV

Yes

Yes

Yes

Yes

Yes

Yes

10 Results available upon request.

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0.743

0.729

0.735

0.744

0.731

0.737

N

50,111

45,495

45,234

50,111

45,495

45,234

Standard errors in parentheses * p<0.1, ** p<0.05, *** p<0.01 Controls are lagged once and DV is lagged twice Table 3: Results of OLS regressions showing the relationship between Migration Potential and logged aid disbursements using observations from 1970-2015. The columns indicate whether Migration Potential was weighted in the model. The red columns include controls and no fixed effects. The yellow columns include both controls and fixed effects.

As cited in the literature review section of this paper, Bermeo and Leblang (2015) find a positive and significant relationship between migration stock, or the size of a migrant population from an aid recipient country living in a donor country, and aid allocations. Their result provides support for two hypotheses: (1) that donors use aid to reduce migration and (2) that migrant populations living in a donor country lobby for their origin country to receive more aid. My results thus far show support for Bermeo and Leblang’s first hypothesis, which echoes my own hypothesis. However, to bolster my argument, I test the costly migration potential variable against migration stock, comparing the explanatory power of each variable in determining aid allocation.

Table 4: Regression Estimates Using Migration Stock as Independent Variable

Time Period

(1) 1970-2017

(2) 1970-2017

(3) 1990-2017

(4) 1990-2017

Interpolated Migration Stock Values (logged, standardized)

0.0295*** (0.00387)

0.0322*** (0.00473)

0.0441*** (0.00412)

0.0476*** (0.00479)

Smooth total trade (logged)

0.101*** (0.0171)

0.0989*** (0.0205)

0.0727*** (0.0193)

0.0174*** (0.0217)

Shared regime type

-0.0439 (0.0348)

-0.0478 (0.0435)

-0.00909 (0.0389)

-0.0118 (0.0457)

Difference in UN ideal points

-0.00994 (0.0348)

0.0129 (0.0406)

-0.0192 (0.0421)

0.0144 (0.0484)

Fixed Effects

No

Yes

No

Yes

Controls

Yes

Yes

Yes

Yes

Lagged DV

Yes

Yes

Yes

Yes

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R-squared

0.705

0.708

0.717

0.720

N

46,880

46,880

31,120

31,120

Standard errors in parentheses * p<0.1, ** p<0.05, *** p<0.01 Controls are lagged once and DV is lagged twice Table 4: Results of OLS regressions showing the relationship between migration stock and logged aid commitments. The red columns represent results from the model run with observations beginning in 1970.

The yellow columns represent results from the model run with observations beginning in 1990.

I find that migration stock, as expected, is a significant predictor of bilateral aid commitments.

However, the coefficients using migration potential as an independent variable are much larger than the above coefficients on migration stock values. To illustrate, in the model using migration potential (weighted, 1500) for observations from 1990-2017, a one standard deviation increase in migration results in a nearly 7% increase in aid commitments, all else equal. On the other hand, a one standard deviation increase in migration stock results in around a 4.5% increase in aid commitments. These results show that the Bermeo and Leblang’s lobbying hypothesis has value in explaining how aid is allocated and complements my hypothesis regarding potential migration and its costs. Migration stock, however, does not replace migration potential. Migration potential and its costs help to provide a more nuanced explanation of how governments allocate aid.

Placebo Test: The Effect of Migration Potential on Multilateral Development Aid

Lastly, I test my model on OECD data encompassing aid commitments from multilateral organizations. This is a placebo test, because it uses the same methodology, but there should be little effect of costly migration potential on multilateral foreign aid commitments. I therefore test following ancillary hypothesis:

Hancillary: The effect of costly migration potential will be stronger on bilateral aid (vs. multilateral).

To carry out this placebo test, I constructed a dataset aid of commitments from EU institutions, the World Bank, and the IMF from 1970-2017. Data are from the OECD. I then tested the effect of migration potential on these commitments. For multilateral aid commitments from EU institutions, I use the migration potentials (and controls) for Germany. I use the United States migration potentials (and controls) to test the effect on World Bank and IMF aid commitments. Results are presented in Table 5 below.

Table 3: Regression Estimates with Logged Aid Disbursements as Dependent Variable, 1970-2017 (1)

(2)

(3)

(4)

(5)

(6)

(4)

(5)

(6)

unweighted

weighted

weighted,

unweighted

weighted

weighted,

unweighted

weighted

weighted,

1500

1500

1500

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Migration

0.0000150***

0.00000429

0.00000398

-0.00000572

-0.00000876

-0.0000103***

0.0000207***

0.0000207***

0.00000888**

Potential

(0.00000264)

(0.00000315)

(0.00000305)

(0.00000799)

(0.00000583)

(0.00000665)

(0.00000309)

(0.00000309)

(0.00000366)

Smooth total

0.145**

0.171

0.210

0.0796

0.0891***

0.0889***

trade (logged)

(0.0132)

(0.0130)

(0.0122)

(0.0175)

(0.0183)

(0.0172)

Shared

0.174

-0.267

-0.182

0.291

0.175

0.245

regime type

(0.159)

(0.296)

(0.240)

(0.239)

(0.271)

(0.278)

Difference

-0.221*

-0.302

-0.261

-0.328**

0.0666

0.006

in UN ideal

(0.0.119)

(0.210)

(0.178)

(0.137)

(0.147)

(0.148)

Fixed Effects

No

No

No

Yes

Yes

Yes

No

No

No

Controls

Yes

Yes

Yes

Yes

Yes

Yes

No

No

No

Lagged DV

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

R-squared

0.504

0.795

0.798

0.679

0.907

0.907

0.512

0.733

0.725

N

1,934

198

198

1,934

198

198

2,435

218

218

points

Standard errors in parentheses * p<0.1, ** p<0.05, *** p<0.01 Controls are lagged once and DV is lagged twice

Table 5: Results of OLS regressions showing the relationship between Migration Potential and logged aid commitments from EU Institutions, the IMF, and the World Bank. The columns indicate whether Migration Potential was weighted in the model. The red columns include controls and no fixed effects.

The yellow columns include both controls and fixed effects. The blue columns include neither controls nor fixed effects.

As expected, migration potential has a much smaller effect on multilateral aid commitments (versus bilateral). The coefficients on migration potential are multiple orders of magnitude smaller than the coefficients from my main model. Migration potential is also an insignificant predictor of multilateral aid commitments when both controls and fixed effects are used. These results prove that migration concerns, significantly expectations of future costly migration, play little role in the decisions of multilateral organizations. This exists in comparison to the above results using bilateral aid, on which costly migration potential has larger effect.

Conclusion

This paper focuses on the relationship between migration and foreign aid, specifically how perceptions of costly migration potential influence how foreign aid donor countries choose to allocate aid.

My theoretical argument highlights that incumbent governments want to avoid costly migration in order to increase their reelection chances. My results confirm that ODA is a foreign policy tool those governments use in an attempt to: (1) reduce the push factors of migration in the migrant origin country, and (2) to signal

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to their electorate that they are taking action to resolve a potential migration that voters may dislike.

These results must still be qualified because of the identification problem presented earlier, namely that there is little exogenous variation in my independent variable, costly migration potential.

My results are important, however, in advancing the link between migration and foreign aid. First, for this project I built a very large dataset of dyadic aid commitments and disbursements. This is the most extensive test of Leblang, Schneider, and Tobin (2019)’s migration potential variable to date. They only test the effect of the variable during the years in which a financial crisis occurred (because they studied the likelihood of bilateral bailouts). Their costly migration potential variable was therefore only tested on around 900 observations. My foreign aid dataset has over 172,000 observations, and my main model is run with 40,000-50,000 observations. Such a large dataset allows for the intensive use of fixed effects and other controls.

While it may seem pessimistic that OECD countries want to avoid migration, especially migration from countries that are ethnically and culturally different from them, it is promising that anti-migration sentiments can be used to justify aid. This paper proves that migration concerns have a role in foreign aid decisions. Using foreign aid to deter migration is a possible alternative to resorting to walls, fences, and other hostile migration policies.

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Appendix Table 1A: Regression Estimates with Logged Aid Commitments as Dependent Variable, 19902015

Variables

(1) unweighted

(2) weighted

(3) weighted, 1500

(4) unweighted

(5) weighted

(6) weighted, 1500

Migration Potential

0.0615** (0.0269)

0.0530* (0.0270)

0.0678** (0.0300)

0.0619** (0.0303)

0.0538* (0.0459)

0.0685** (0.0343)

Smooth total trade (logged)

0.0860*** (0.0200)

0.0882*** (0.0228)

0.0816*** (0.0203)

0.0853*** (0.0227)

0.0876*** (0.0264)

0.00812*** (0.0239)

Shared regime type

-0.00667 (0.0358)

-0.00967 (0.0398)

-0.00591 (0.0378)

-0.00767 (0.0420)

-0.00838 (0.0486)

-0.00459 (0.0466)

Difference in UN ideal points

-0.00478 (0.0403)

0.0178 (0.0398)

0.0236 (0.0386)

-0.00270 (0.0462)

0.0208 (0.0460)

0.0257 (0.0449)

Fixed Effects

No

No

No

Yes

Yes

Yes

Controls

Yes

Yes

Yes

Yes

Yes

Yes

Lagged DV

Yes

Yes

Yes

Yes

Yes

Yes

R-squared

0.714

0.686

0.701

0.717

0.689

0.704

N

31,116

27,338

27,149

31,116

27,338

27,149

Standard errors in parentheses * p<0.1, ** p<0.05, *** p<0.01 Controls are lagged once and DV is lagged twice Table 1A: Results of OLS regressions showing the relationship between Migration Potential and logged aid commitments using observations from 1990-2015. The columns indicate whether Migration Potential was weighted in the model. The red columns include controls and no fixed effects. The yellow columns include both controls and fixed effects.

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Facebook and Electoral Success: Evidence from Germany Ava Vecellio

This paper analyses the possible effects of political parties’ social media post fre- quency on electoral vote share. It begins with a cursory analysis of social media usage, especially in the realms of news consumption, and an explanation of Germany’s political parties and electoral system. It then examines various literature relating to the topic of social media and politics. The hypothesis of this paper predicts that there is a positive relationship between the number of social media posts and electoral vote shares (meaning that a higher number of social media posts would result in a higher vote share for the political party who curates said posts). The data illustrates this positive relationship using beta coefficients and finds that an increase in one standard deviation in total Facebook posts was significantly correlated to a .199 rise in standard deviation for the party vote share for the Landesstimme (LS) vote during the 2019 Thüringen state election.

Introduction

The proliferation of social media usage in recent years has marked an astonishing transformation in global communication, but the importance and influence of social media in various circles of life is not yet entirely known. This paper explores social media’s effect on electoral vote share. For this reason, the introductory section of this paper explores several facets of social media, especially in regards to its usage and credibility as a source of news. This section also gives a cursory explanation of Germany’s politics.

Thüringen, Germany, is the location of the data used in this paper’s analysis.

68% of Americans use Facebook, a notable amount considering the websites relatively recent founding in 2006. About three-fourths of the 68% are daily Facebook users [20][5]. Particularly notable for this paper are the avenues in which social media has affected the way users communicate and receive information on many different levels. Not only has social media birthed the opportunity to maintain close ties with family members and friends, but it also allows users to communicate with some of the most well-known figures of the current day, from major celebrities to high-ranking politicians. Generally, political activism and communication has been almost entirely redefined by the emergence of social media platforms. The 2016 election of Donald Trump illustrated the power of social media as a political tool for politicians; Trump used Twitter as a free channel to speak openly and bluntly to constituents and critics alike instead of more traditional forms of presidential communications such as White House Press conferences [19]. As of January 10, 2020, the last formal White house briefing was March 11, 2019.

Stephanie Grishman, who was press secretary until April 2020, had yet to hold a briefing since receiving

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the position [13].

Just as the rise of social media has changed the way politicians across the world communicate with their various constituencies, it has also changed the way in which individuals receive information, the most pertinent type of information for this particular paper being news and/or political information. A 2017 PEW research survey found that social media was a source of news for approximately two-thirds of the United States population [18]. Even from 2016 to 2017, there was a two percent increase in adults who use social media to get news often (18% to 20%) and a one percent increase in adults who use social media to get news sometimes (26% to 27%) [18]. Additionally, from 2016 to 2017, Americans aged 50 and above, had a significant increase in the population who received news from social media (45% to 55%) [18]. Those 50 and under had no change from 2016 to 2017, but their level of news-based social media usage remains higher at 78% [18].

However, it is vital to note that all the above statistics were gathered from the United States population. This paper focuses on Germany, which has a different relationship with social media. As compared to the 67% of Americans who use social media as a source of news, only 31% of the German population uses social media as a path of media consumption. Although the country is not as social media dependent as the United States, the growth of social media in Germany is still of particular importance, especially given the fact that social media is viewed as a main source of information for Germans ages 1834 [6].

In order to explore how social media websites affect politics, a basic understanding of the platforms is needed. Facebook, originally thefacebook.com, launched on February 4, 2004 for Harvard students as a way to connect and maintain contact with fellow students [5]. In September of 2006, Facebook expanded to allow access to any individual over the age of 13 [5]. The site has continued to expand and logged a monthly active user count of 2.2 billion during 2018’s first quarter [6]. Similarly, Twitter debuted in March of 2007 and, at the start of 2019, had a daily active user count of 126 million [22][17]. These numbers are significant, especially in the realm of politics and news dissemination.

In order to understand the importance of how Germany political parties use social media, it is vital to also understand the politics of each of Germany’s political parties. Below is a brief explanation of each political party explored in this paper’s analysis [17][15][16]: Table 1: German political parties

Political position

Seats (federal parliament)

Pol (Thüringen's parliament)

CDU

center-right

200

21

SPD

center-left

152

8

The Greens

center-left

67

5

The Left

left-wing

69

29

AfD

right-wing/far right

92

22

Germany’s political parties are also active on social media platforms. The power of these

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platforms is a complex issue to dissect. Social Media Report: The 2017 German Federal Elections does an in-depth analysis of the Twitter and Facebook pages of seven political parties: The Greens (die Gru¨nen), the SPD (Sozialdemokratische Partei Deutschlands), the FDP (Freie Demokratische Partei), the CDU (Christlich Demokratische Union Deutschlands), the Left (die Linke), CSU (Christlich-Soziale Union in Bayern), and the AfD (Alternative fu¨r Deutschland). While the AfD had the lowest Twitter follower count of any of the parties by a large margin, it had the most prominent presence during the election period, accounting for over half of party name mentions and hashtags [6]. The Green party, on the other hand, has the most followers, but only accounted for 2.75% and 2.07% of each of those categories, respectively.

On Facebook, AfD also dominated, having the most active users, comments, likes, and shares [6]. The AfD had an overwhelming majority of supporters in many of these categories, far beyond any other party. For example, the AfD had over 700,000 Facebook comments while the next highest numbers. The CSU had only just over 200,000 comments. This situation is also seen in the number of shares: the AfD had over 1,000,000 shares of Facebook posts while the next highest number of shares was just over 200,000 shares for the SPD.

Figure 1: Facebook reachability of different German parties – “Upper left: Number of unique users that have either commented or liked a post in the Facebook pages. Upper right: Number of likes per party.

Bottom left: Number of comments, including comments on comments. Bottom right: Number of times that the party posts were shared.” [6]

Another important note to cover in this introduction is an explanation of Germany’s electoral system. The electoral system of Thüringen, the specific German state analyzed in this paper, reflects the federal German electoral system. This system is complex, especially compared to the U.S. electoral system,

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so the following paragraph attempts to explain this system in relation to how it effects the findings of this paper.

At the federal level, citizens are given two votes for an election: the “Erststimme” and the “Zweitstimme.” The same is true for state elections in Thüringen, although the votes go by different names: the “Wahlkreisstimme” and the“Landesstimme”. The “Wahlkreisstimme” is a vote for a specific candidate while the “Landesstimme” vote is a vote for a party. Seats in the state Bundestag are assigned by calculating the percentage of votes each party received [8]. For example, the Left party had a vote share of 31% overall in Thüringen and received 18 seats in parliament as a result of that percentage of vote share [21]. This paper specifically looks as the “Landesstimme” vote, which will be followed by the abbreviation LS from this point forward, and the percentage of “Landesstimme” (LS) votes garnered by each party in each district in Thüringen. The “Wahlkreisstimme” is not examined in this paper, however, future research could look into whether these two votes are affected differently by social media usage by parties and candidates.

This above information regarding the German State electoral system is vital to understand, as this paper examines the election in Thüringen, Germany which took place on October 27, 2019. The paper regresses the electoral vote share for five parties’ “Landesstimme” (LS) vote in 23 districts on the sum of daily Facebook posts (from a party’s district Facebook page) and hypothesizes a positive correlation.

This hypothesis is supported by the data in this paper using beta coefficients, which illustrated a positive correlation of .199.

As this introduction discusses, social media has seen a rapid growth in importance in both the United States and Germany, including in the realm of news consumption. Young people in both countries are particularly likely to use social media as a source for news content. This importance of social media in the realm of politics has not gone unnoticed by political parties in both countries, which use websites such as Facebook and Twitter as a new and efficient way to reach constituents and discuss important topics.

However, as the literature review of this paper will explore, the social science literature surrounding social media and politics is new and emerging. This makes this particular realm of research wildly interesting, but also puts a limit on the casual implications one can draw from this paper. However, as this introduction highlights, social media is only growing in importance in people’s lives, especially in how we come to read and understand politics. Overall, the study of the intersection between social media and politics is new and complex, especially in its endogeneity. This makes the finding of concrete causal links difficult, but continued data collection and research is vital in the search to find the answers to these important questions. This paper can serve as a foundational piece in the study of if and how political parties can use social media to increase their vote share and overall electoral success.

Literature Review

The literature surrounding the topic of politics and social media is a new and emerging field. For this reason, the literature review is not as robust as those exploring more traditional forms of political social science research. However, there has been a relatively recent proliferation of research that has yielded interesting results. Much of this literature review centers around social media’s ability to translate into the real world and affect politics.

The effect of social media messages and their political implications, such as voting, have been studied for several years. Studies in 2010 and 2012 illustrated a positive effect on real-world voting from

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AVA VECELLIO

online posts encouraging voting. Bond, R., Fariss, C., Jones, J. et al (2012) explores this relationship through a randomized system that messaged over 60 million Facebook users and found these messages affected a number of the user’s action including voting behavior [4]. Jones, Bakshey, Eckles, and Fowler (2017) also looked at this relationship in the 2012 U.S. presidential election. They found that, despite the over-saturation of political messaging on many platforms due to the fact that 2012 was the year of a presidential election, these message still had a positive effect on voting behaviors [11]. Both papers further explore the fact that these messages also positively affected the voting behaviors of the receiver’s friends [4][11]. These findings point towards social media’s power to affect the outside world and, namely, the ability for messages and/or posts to affect the actions of the receivers and their broader circle.

Other researchers have explored this phenomenon in a non-United States context. Bakker de Vreese (2011) analyzed the relationship between media usage and political participation from online survey data in the Netherlands [2]. The study found that there was a positive, significant correlation between online news reading and political participation [2]. The use of social networks, however, was not significantly correlated in this paper [2]. Arriagada, Scherman (2012) focused on Chile and found that Facebook had a significant and positive correlation with increased protest activity [23]. Both of these papers support the idea that media usage, including perhaps social media, translates to real-world actions with significant political implications.

Other papers have also explored social media as a predictor of civic participation and behavior.

Zúñiga, H. G. D., Jung, N., Valenzuela, S (2012) found that media use was significantly correlated with civic participation, even when controlling for variables such as age, gender, race, income, and education [25].

Another study also by Zúñiga sought to replicate these results with success. Using panel data, this paper found a positive correlation between social media, specifically social media as an informational tool, and political participation beyond an online environment [26].

DiGrazia, McKelvey, Bollen, Rojas (2013) explores a possible relationship between social media and electoral results. They found that in both a bi-variate and a full model that an increase in Twitter shares, which is the amount a candidate was mentioned in the random sample of analyzed tweets, was correlated with an increase in vote share [7]. The authors explore this relationship as that of an indicator, meaning social media reflects political behavior. However, this relationship could also be theorized to be one that shows how social media can affect political behavior by encouraging voting or shifting political opinions through Twitter discussions that center around political candidates.

Haenschen (2017) explores how social pressure on Facebook can affect voter turnout. In three separate studies, pressure exerted via Facebook was correlated with an increase voter turnout [10]. This is especially significant for this paper as voter turnout could be a potential avenue through which party Facebook posts could shift the vote share for an election. Another potential avenue is that Facebook posts simply change the part of the electorate that is voting, rather than increasing voter turnout in totality,.

Social science research papers have also explored how social media usage affects real-life actions outside of various types of civic participation, such as voting in elections. One example is Mu¨ller and Schwarz (2017), which analyzed Facebook data to explore whether anti-refugee ideas affected hate crimes against refugees [12]. The paper found that, when comparing similar municipalities, these anti-refugee sentiments did predict hate crimes against refugees. Power outages, which would limit one’s access to Facebook, were used as an exogenous variable that could attempt to establish a causal link [12]. The paper found that during these outages, in areas with high Facebook usage, a greater amount of online

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anti-refugee sentiment was not significantly correlated with an increase in hate crimes [12]. The authors concluded that this observation points to social media as “propagation mechanism” in how online antirefugee sentiment becomes real-life violence against refugees [12].

Social media has also been explored as a potential predictor of election results as compared to tradition polling results with limited success. An example of this type of research is Veps¨al¨ainen, Li, and Suomi (2017) which used Facebook likes as a predicting measure and found it to be less accurate than both incumbency and polling predictions [24].

Social media research has also examined the types of posts that are shared, especially from new and rising far-right parties, such as those in Europe. Ben-David and Matamoros (2016) found that extreme right parties in Spain had a greater frequency of insulting language and visual content [3]. Mu¨ller and Schwarz (2017), which was discussed in more detail in an earlier paragraph, also found anti-refugee posts on the main Facebook page for Alternative fu¨r Deutschland (AfD), the new far-right German party that has gained major prominence, especially after the 2017 federal election where it secured enough seats to become the third largest party in the Bundestag [12][14]. This research is vital in understanding what posts gain traction. It allows for studies to be done to see if such posts inspires more or less real-world activities such as protests or voting.

The ability of social media to possibly encourage real-world voting and other political behaviors also poses an interesting question on how political campaigns can marry the use of social media with other, more traditional forms of campaigning such as canvassing and phone banking, in order to run the most efficient and successful campaign possible [9]. Gerber, A. S., and D. P. Green found that canvassing, where personal contact was made, increased voter turnout by between 6% and 7% and further calculated an average cost of about 16 dollars per additional voter gained via canvassing [9]. This can be compared to research exploring the effectiveness of both social media advertisements and social media pages. Further research should be done to understand the change in voter turnout in relation to these two online avenues as well as their cost effectiveness, especially given the fact that a campaign could run a social media page, in theory, for free. If social media continues to grow in use and importance as it has in recent years, these avenues will also like only grow in importance and if these options prove to be more cost effective, they could transform the way in which politicians and parties engage in political advertising.

Explanation of Strategy and Data

This paper examines the 2019 election in Thüringen, Germany which took place on October 27, 2019. This paper’s independent variable is the sum of daily Facebook posts (measured from October 1 through October 26) from party Facebook pages for five German political parties in Thüringen's 23 Landkreise (districts). The parties examined in this paper are Alternative für Deutschland (AfD), Die Linke (the Left), Die Sozialdemokratische Partei Deutschlands (SPD), Die Grünen (the Greens), and Die Christlich Demokratische Union Deutschlands (CDU).

As discussed in the introduction section of this paper, this regression uses the Landesstimme (LS) vote share as its dependent variable. The Landesstimme (LS) vote is the vote cast for a party rather than a particular candidate. Data for the dependent variable, the vote share, was pulled from Thüringen's official electoral website which contains information regarding Thüringen in European elections, federal elections, state elections, and communal elections. Vote share is measured at the district level and Thüringen has a total of 23 districts and free cities which are pictured below:

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Figure 2: Districts and free cities in Thüringen

For this paper, Facebook was chosen as the social media platform of interest, because it is the largest social media platform in Germany [6].

Figure 3: Alternative für Deutschland (AfD) Erfurt Facebook Page

Figure 3 is an example of the Facebook pages from which data was collected. This was the page used to represent the AfD party in the district of Erfurt. The number of daily posts from October 1 to October 26 were collected by hand by me through Facebook’s website. As shown in this example, these

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Facebook pages represent at party in a district in Thüringen rather than one specific candidate.

Pages were found through Facebook’s search platform. Most often, pages were found by searching the district of interest and the party’s abbreviation. Referring once again to the example pictured above, this page could be found on Facebook by searching a combination of Erfurt and AfD.

For my regression, I used the following controls: incumbency, asylum seekers as a percent of the population, population 60 and over, population 18- 25, unemployment rate, and the log of the GDP. A one percent sample of each district’s population with a bachelor’s degree or higher was also used as a control.

This was the only college-level educational data available at this level and, for the purposes of this paper, is assumed to be representative of the entire population of this district. This is, however, a clear limitation to this paper. All controls were measured at district level and added to the regression on at a time. All control variable data was pulled from Thüringen's statistical website, Thu¨ringer Landesamt fu¨r Statistik. I also added fixed effects for constituency and party.

When accounting for the explanations and variables listed above, the full regression regresses the “Landesstimme” (LS) vote share on the sum of daily Facebook posts while controlling for the incumbency effect of a party, the percent of asylum seekers compared to the population, the population of people both 65 years of age and older and ages 18-25, the number of individuals in the population with a bachelor’s degree or above, and the log of the GDP. The regression has 115 observations.

Null Hypothesis: Facebook post frequency will have no effect on Landesstimme (LS) vote share.

Hypothesis 1: Facebook post frequency will have a positive effect on Landesstimme (LS) vote share.

However, there are many aspects that could potentially affect a party’s vote share for any particular election. One major example of such an aspect with a rich research history is incumbency status. Social media presence is only one of these aspects. It is also relatively new and evolving and possibly connected to other variables that affect vote share. Additionally, the level of change for the independent variable this paper’s regression, when not using beta coefficients, is one additional Facebook post. For these reasons, I do not expect Facebook post frequency to have particularly large effect on total vote share.

Hypothesis 2: Facebook post frequency will have a positive, but overall small effect on Landesstimme (LS) vote share (less than 1%).

Results

For this paper, control variables were added one at a time into the regression. Party and district fixed effects were used in all regressions, except the first (column 1 in Table 3) which examined just the independent and dependent variables.

Based on my results, I was able to reject my null hypothesis that Facebook post frequency would have no effect on Landesstimme (LS) vote share with at least 95% confidence. This rejection occurred on all regressions run for this paper, as the relationship between Facebook post frequency and Landesstimme (LS) vote share was significant in all regressions, including when all controls and fixed effects were added.

In all of the regressions, the explanatory variable (total sum of Facebook posts) is statistically

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significant using beta coefficients. In the final regression (column 8 in table 3), the explanatory variable is significant and has a coefficient of .199 with a P-value of .01. This means that an increase in one standard deviation for total daily Facebook posts is correlated with a .199 increase in standard deviation for the vote share for that party.

The only other statistically significant variable in the regression is incumbency. In the final regression (column 8 in table 3), incumbency had a coefficient of .212 with a P-value of .001; based on this, if a party was the “incumbent”, meaning in this case that they received the most votes in the 2012 election in Thüringen, there was a correlated .212 increase in the standard deviation for the vote share of that party.

All other control variables used in the regression were insignificant. However, the party fixed effects were statistically significant, either to the .001 level or the .05 level, indicating that differences in the parties, such as platform and party-issues, have a significant effect on the percentage of Landesstimme (LS) vote share received by that party, which is a logically sound result. I also tested for interaction effects among all control variables and found no significant interaction effects between the independent variable and any of the control variables used in this regression.

The results of this research confirm both hypotheses set out in this paper. Facebook post frequency did have a positive effect on the vote share, confirming hypothesis one. However, this positive correlation, when not using beta coefficients, was .0364. This is just over 3/10ths of one percent of the vote share, which is not a very large change. However, it is important to note that the explanatory variable increases in increments of one (meaning one Facebook post) and that the correlation (.0364) is the effect of one additional Facebook post. This could be a potentially strong correlation if a party were to use Facebook effectively and regularly.

Table 2 is a balance table that looks at the means of all control variables above and below the media of the explanatory variable, the sum of the total daily Facebook posts. None of the variables have significant differences in their means, indicating no relationship between the explanatory variable and the control variables.

Table 3 is the main results of the regressions. Each regression adds a new control variable to the equation as indicated in the graph.

Conclusions

This paper offers compelling results in research regarding the effect of social media on electoral outcomes. While it is difficult to draw casual links with social media research due to the inherent endogeneity of social media, the field of social media is of great importance in politics and a relatively new field. These facts highlight the importance of research even if such research does not lead to clear causal results. Therefore, although this paper does not attempt to draw a clear causal link between Facebook post frequency by political parties and those parties’ vote share, I believe this paper adds greatly to the literature surrounding the electoral effects of social media.

Additionally, this paper includes a large amount of hand collected and organized data that could be used significantly in future papers and research. This means, while the correlations in this paper cannot be connected via a causal link, the collection of this data is, regardless, a significant contribution to the field. This data can be used in future research or can be used as a model of how to conduct social

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science research on a limited time and financial budget that makes the use of tools such a digital scraper an impossibility. Simple, hand-collected data looking at variables such as total number of posts or percentage of reaction type (i.e., like versus angry react on Facebook) can pose interesting questions about social media and politics while also being accessible to all individuals interested in research, particularly students.

Originally, there was a plan to include text-sentiment analysis of popular Facebook posts from the German parties in this paper. However, I was unable to finish this aspect of the paper due to time constraints. I believe it is worthwhile to examine popular Facebook and Twitter posts from major parties across the world in order to understand what types of language receives the most interactions online. Based on this research, further regressions can be run examining the effects of posts containing high-interaction and low-interaction language on electoral vote share.

Another interesting point of future research could be the idea of spillover effects. Since social media has no clear geographic barriers on what users can like, it is possible that activity on Facebook pages of neighboring districts or even districts in an entirely different area could affect vote share in a different district. It would also be interesting to explore how country-wide Facebook pages, such as the official AfD page for the entirety of Germany, may affect vote-share in smaller elections and whether their influence is greater or lesser than local pages. Overall, the complex landscape of social media and the wide range of opportunities to find both local and global accounts and pages raise many questions and future research possibilities regarding how online activity can be translated into real-world political actions.

Further research should be done continuing to look at posts on Facebook, as well as other social media sites such as Twitter and Instagram. Potential research into instrumental variables could also prove vital in creating a research plan that is able to draw casual claims.

Research has indicated the power of social media in affecting real-world actions and with no indication that social media growth will be halted in the future, candidates’ and political parties’ understanding of how their pages affect issues such as vote share could prove vital in electoral success.

Additionally, understanding the importance of social media posts could prove incredibly important in campaigning, especially in small and/or independent campaigns, as it could help reveal the most effective methods to reach and enliven voters (i.e. phone banking, canvasing, social media posts and/or ads, television ads) and therefore the most effective way to spend one’s budget.

Overall, this paper provides interesting results that are statistically significant, but is not able to draw clear casual claims regarding daily Facebook post frequency and electoral vote share. This paper, however, provides a groundwork for future research and adds a new question to the literature regarding how social media affects politics. More research in this area is not only encouraged by this paper but needed in the adaptation and evolution of politics in this growing digital age.

Appendix

Table 2: Balance table of controls

Incumbency

(0) Below Median

(1) Above Median

(2) Difference

0.21 (0.05)

0.19 (0.05)

-0.021 (0.075)

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AVA VECELLIO

Percent Asylum seekers in population

0.37 (0.03)

0.35 (0.02)

-0.022 (0.035)

Population with bachelors degree or higher

11.96 (1.11)

14.32 (1.61)

2.392 (1.921)

Percent of population over 65

26.04 (0.30)

26.22 (0.37)

0.179 (0.481)

Percent of population 18-25

0.524 (0.14)

5.44 (0.19)

0.206 (0.242)

Unemployment Rate

11.08 (0.32)

11.47 (0.38)

0.388 (0.495)

Log(GDP)

7.81 (0.05)

7.8 (0.06)

-0.013 (0.078)

Total number of observations

57

58

115

Table 3: Regression results

Total daily posts Incumbency

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

0.134**

0.134***

0.199**

0.199**

0.199**

0.199**

0.199**

0.199**

(-3.34)

(-3.34)

(-3.34)

(-3.34)

(-3.34)

(-3.34)

(-3.34)

(-3.34)

0.215*** 0.215*** (-5.05)

Percent Asylum seekers in population Population with bachelors degree or higher Percent of population over 65

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0.212*** 0.212***

0.212***

0.212*** 0.212***

(-5.05)

(-3.94)

(-3.94)

(-3.94)

(-3.94)

(-3.94)

-0.00117 (-0.01)

0.17 (-0.92)

-0.0139 (-0.29)

0.0867 (-0.08)

0.0324 (-0.27)

-0.121 (-0.16)

-1.432 (-0.74)

0.435 (-0.22)

0.129 (-0.3)

0.835 (-0.36)

1.81 (-0.37)

-0.189 (-0.51)

-0.129 (-1.01)

-0.374 (-0.40)

-0.927 (-0.39)

FACEBOOK & ELECTORAL SUCCESS

Percent of population 18-25

-0.0588 (-0.19)

Unemployment Rate

43

-0.507 (-0.34)

-1.279 (-0.36)

0.155 (-0.28)

0.05 (-0.45)

Log(GDP)

-2.698 (-0.37)

Constant

0.428

0.429* (-2.45)

0.428** (-3)

-0.194 (-0.22)

0.769 (-0.66)

0.551** (-3.4)

0.682 (-1.53)

22.25 (-0.38)

Total number of observations

115

115

115

115

115

115

115

115

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Reinterpreting the Varieties of Capitalism from Germany's Radical Innovation Myung Ha Kim

This study argues that the reason for Germany’s competitive edge in radical innovation in the current digital era resides in the hybridization of national institutions. This follows to disprove the traditional Varieties of Capitalism (VoC) approach, which argues that firms in coordinated market economies (CME) specialize in incremental innovation while firms in liberal market economies (LME) specialize in radical innovation. This paper first presents the U.S. and Germany’s latest performance in radical innovation between 2012 and 2018. It proceeds to provide a qualitative case study by examining the U.S. and Germany’s contemporary domestic institutions—labor market structure, prominence of innovation clusters, the resilience of start-up ecosystem—to account for how Germany has gained its competencies in radical innovation over the past seven years. This study concludes that today’s successful digital innovation rests heavily on the existence of an institutional setting propitious to radical innovation.

Introduction

In recent years, many advanced industrialized countries have devoted much to gain competitiveness in the high-tech sector such as artificial intelligence (AI), robotics, internet of things in the advent of the fourth industrial revolution (Schwab 2016). These advanced technologies are the key contributors to economic productivity. Dominance in this area requires a country’s capacity for disruptive innovation and adopting fast-moving technologies (Lee et al. 2018). The United States (U.S.) and Germany are currently the two major countries leading global innovation. Although the U.S. and Germany have been competitive in the era of digital transformation, the two countries have long appeared to have disparate corporate governance structures (Hall and Soskice 2001). This leads to an empirical puzzle: Why have Germany and the U.S. both become dominant players in radical innovation despite their distinct political economies? The following research questions include: Are there common institutional features that contribute to the two countries’ competitiveness in radical innovation? Can Germany successfully achieve radically innovative breakthroughs without discarding its embedded highly coordinated institutions (if so, how)? This paper addresses these questions by comparing today’s innovation systems in Germany and the U.S.

Since this paper aims to explain the innovation systems in two countries with particular attention to the current digital era, the paper’s scope is limited in the time period between 2012 and 2018. The reason for this selection is to cover the period after Germany’s announcement of national innovation agenda, Industrie 4.0, in 2011 and the U.S.’s innovation plan in 2015 (The White House 2015; European

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MYUNG HA KIM

Commission 2019). Drawing from the VoC framework, this investigation focuses on the role domestic institutions played in national innovative capacity, excluding international factors germane to innovation.

Specifically, this paper argues that three institutional domains in domestic political economy—labor market structure, innovation clusters, start-up ecosystem—can account for Germany’s recent achievements in radical innovation.

This paper is organized as follows. The next section provides a literature review on the VoC approach with regard to national innovation behavior. The third section presents the U.S. and Germany’s current performance in radical innovation, which is the dependent variable in this paper, measured by patents applied/granted in each country. The following sections explain domestic institutional features, the explanatory variables that have contributed to success in radical innovation, ending the discussion with conclusions.

Literature Review

Varieties of Capitalism and Innovation Systems

The VoC approach posits that liberal market economies (LME) and coordinated market economies (CME) have comparative advantages in radical innovation and incremental innovation, respectively (Hall and Soskice 2001). Hall and Soskice refer to radical innovation as the development of entirely new products and revolutionary change in production, while incremental innovation refers to gradual improvements in existing product lines. The dichotomy is due to the long-standing comparative institutional advantage in U.S. (LME) and Germany (CME). The key institutional characteristics of LME such as the U.S. include flexible labor market settings, shareholder maximizing equity markets, which are propitious to producing new, disruptive technologies. On the other hand, CMEs, characterized by highly coordinated industrial-relations and skill training systems, are better suited for innovation through smallscale improvements in existing products (Hall and Soskice 2001).

National political and economic institutions definitely play a central role in a country’s innovation performance, and many scholars have examined cross-national variations in innovation outputs based on the VoC framework (Allen et al. 2011; Casper et al. 1999; Casper and Whitley 2004; Ebner 2010; Sternberg et al. 2010). Casper, Lehrer, and Soskice (1999) identified that the U.S. and Germany’s innovative capacity is determined by labor market relations, company law, skill formation, and financial system, the national institutional framework differentiating LMEs and CMEs. Due to the existing institutions of deregulated labor markets, high-risk tolerance, the authors explain that the U.S. has been better situated to develop high-tech industries, such as software products and therapeutics. In Germany, which has a collective bargaining system and relatively more risk-averse investments, innovative breakthroughs are less likely, and so innovation generally gears towards platform technologies—such as those used in therapeutics and software services.

The validity of classifying national innovative behavior into incremental and radical innovation has been intensely debated among scholars. Some scholars have at least partially supported the dichotomy of incremental and radical innovation behaviors in CME and LME countries (Hermann and Peine 2011; Pyka et al. 2016), but many have presented contradictory empirical results that the VoC approach does not necessarily hold true and needs to be reinterpreted (Akkermans et al. 2009; Allen et al. 2011; Casper and Whitley 2004; Fritsch 2015; Taylor 2004;). Taylor (2004) showed an empirical test based on patent data

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that the dichotomy between LME and CME in innovation behavior only becomes apparent when the U.S. is included in the analysis. When the U.S. is excluded from LME, the remaining LME countries do not necessarily perform better in radical innovation than CME counterparts. In fact, CME countries such as Japan and Germany are found to be more competitive in the high-tech sectors than LME countries without the U.S. The argument that national technological specializations are heterogenous and thus blurring Halls and Soskice’s dichotomy was later advanced by another empirical test by Akkermans, Castaldi, and Los (2009). In truth, it turns out that the presence of work councils, collective bargaining systems, which are the central characteristics of CME, are not obstacles to radical innovation (Casper and Whitely 2004) for instance in the German pharmaceutical industry (Allen et al. 2011).

A recent empirical study by Witt and Jackson (2016) identifies inherent problems associated with LME and CME systems and suggests that each corporate governance system could benefit from adopting certain institutional features from one another. Based on their analysis in trade patterns of comparative advantage in products from radical innovation between 1995-2003, Witt and Jackson found that the reason for Germany’s high performance in radical innovation such as chemicals and motor vehicles is due to the hybrid combinations of liberal institutions (LME) such as strong shareholder protections and coordination (CME) in employment relations, education and skills. Their study argues that Hall and Soskice’s typology has less explanatory power to account for cross national variations in innovation behavior. Witt and Jackson’s argument is also backed by a study on the successful performance of the American subsidiary companies in Germany in radical innovation and that the host country’s CME-specific employment structure did not block radical innovation but rather, the combination of LME and CME institutions allowed the firms to achieve radical innovation (Backes-Gellner et al. 2016).

This institutional hybridization of traditional German institutions is depicted by the gradual adaptation of flexibility in corporate governance without completely discarding CME institutions such as coordination interfirm networks, education and training was a necessary response to the changing circumstances by globalization (Ebner 2010; Fritsch 2015). A similar finding was documented in a qualitative study by Ornston (2012), who argues that the reason for Nordic CME countries’ success in the high-tech sectors during the 1990s is their institutional adaptation of venture capital, multi-stakeholder cooperation. As such, institutional change in the Nordic CME countries was driven by the changing circumstance of economic downturns back then (Ornston 2012). In Germany, deregulation has affected corporate profitability in the high-tech sector, which prompted companies like Siemens to modify their risk-aversive culture to one that is more profit maximizing oriented in order to spur innovation (Fritsch 2015). However, Fritsch (2015) maintains that such firm-level “contingent institutional adaptation” did not bring complete dismantlement of CME characteristics, as consensus-based management practices were maintained intact in Siemens.

This paper attempts to advance the existing scholarship on national innovation behavior by examining Germany and the U.S.’s innovation systems in this distinct era of digital transformation, where countries’ endeavor for radical innovation becomes more conspicuous. The existing literature provides valuable insights into domestic institutional mechanisms for innovation, yet it is limited in the scope of their analysis, primarily in time periods before the inception of countries’ new innovation agenda for the fourth industrial revolution. In this regard, this study incorporates today’s national innovation behavior into changing institutional trajectory; i.e. examining hybridization of institutions/converging response to digital transformation through the lens of Germany and the U.S.’s approaches to radical innovation. Based

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on more recent data on patent applications during the time period between 2012 and 2018, this paper provides updates on the institutional framework that drives high-tech industries, particularly in Germany.

Seeking to undercover key factors contributing to radical innovation, this paper looks at three different domains—industrial relations; innovation clusters; start-up ecosystem. This study is expected to help our understanding of the U.S. and Germany’s innovation performance by linking them to three political economic institutional domains, which arguably have not been sufficiently explored in the CPE literature.

U.S. and Germany's Innovation Performance in Disruptive Technologies

This paper uses patent counts as a measurement of the U.S. and Germany’s performance in radical innovation, given many previous studies have used patents to evaluate the radicality of countries’ innovation outputs (Akkermans et al. 2009; Casper et al. 1999; Grashof et al. 2019; Taylor 2004; Witt and Jackson 2016). Since a patent is a type of an intellectual property right exclusively given to the owner of new inventions, a higher number of patents applied and granted indicates the country’s success in radical innovation (Taylor 2004). The patent data used here are from the World Intellectual Property Organization (WIPO) and the European Patent Office (EPO) databases. This section attempts to show how Germany has revealed its competitiveness in radical innovation based on the patent counts over the past seven years, 2012 to 2018. To be clear, this section does not aim to prove that Germany outpaces the U.S. with respect to radical innovation, but rather is used to illustrate the recent trends in Germany’s activities in radical innovation.

According to Figure 1, U.S. and Germany are leading countries in patents applications. The U.S. currently has the biggest number of applications, which occupies 25 percent of global patents, followed by Germany with 15 percent global share. In absolute term, the U.S. outpaces other countries significantly.

This becomes clear as U.S., an LME country, has long been known for its status as the global innovation powerhouse. Although being number two in the global patent filing is a notable result for Germany as a CME country, the difference in the shares between the U.S. and Germany seems significant. However, when the patent counts are compared by the number of patents application per million population, Germany is not necessarily lagging behind the U.S., as figure 2 shows.

Figure 2 shows the rivalry in patents application counts between Germany and the U.S. between 2012 and 2018—the patent counts used here are based on the counts by the applicants’ origins of country.

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The two countries are close pitched in radical innovation given the differences in patent counts only to a small extent. This indicates that Germany has stayed competitive against the U.S. in patent activity. When it comes to the number of patents granted, which refers to the legally effective patents after the necessary examinations on patentability by the patent office, Figure 3 shows that Germany is producing even more granted patents than the U.S. during the same time period.

A closer look at this performance can be seen in Figure 4, which compares the number of patent grants in the two countries in four different areas of technology. The rationale for the selection of these specific four sub-sectors of technology is as follows. Telecommunications, semiconductors, biotechnology are chosen for comparison, since scholars have traditionally referred to the performance in these fields of technology as radical innovation (Hall and Soskice 2001; Casper and Whitley 2004; Taylor 2004). In particular, telecommunications and biotechnology are important areas for their radicality in the current era of digital transformation because they are the most popular fields where AI technologies are applied for new inventions (WIPO 2019). On the same ground, transportation is also included given its relevance to the application of AI technologies such as in autonomous vehicles and driver recognition (WIPO 2019). In fact, the WIPO’s recent report on technology trends in AI states that 42 percent of all filed patents relevant to AI came from telecommunications, transportation, and medical sciences, which include biotechnology (WIPO 2019). Semiconductors are relevant to radical innovation today as well, since disruptive inventions

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in memory chips become hardware that expediates the AI technologies (Batra et al. c).

Figure 4 reveals Germany’s relative competitiveness in transport and the U.S.’s comparative competitiveness in the telecommunications and biotechnology sectors. The difference in patent counts in semiconductors is not significantly noticeable between the two countries. This figure on the latest performance in four different sub-sectors are very distinct from Hall and Soskice’s patent data analysis between Germany and the U.S. during 1983-4 and 1993-4, which found Germany to be less specialized in semiconductors, biotechnology compared to the U.S. (Hall and Soskice 2001). This suggests Germany has not lagged in disruptive innovation. Thus, the results provide updated empirical evidence in addition to the previous studies that debunked the VoC dichotomy (Taylor 2004; Akkermans et al. 2009; Allen et al. 2011).

Based on the latest patent activity over the past seven years, Germany appears to have had a competitive edge in radical innovation.

Paths to Radical Innovation

Labor Market Regimes: Workforce Flexibility and Vocational Training

Power, hegemony, and authority are all concepts which merit discussion in the context of

conflict, but with Innovation hinges on both incumbent and workers’ cumulative experience and skills, and knowledge about the latest technologies. Recruiting and retaining knowledge talents are thus important for firms to keep abreast of new ideas and to adopt and implement them to develop novel technology.

The traditional VoC approach distinguishes LME and CME in this domain of workforce management.

LME has a highly deregulated labor market, low hiring and firing costs and higher flexibility in managing human resources, which have led to a comparative advantage towards radical innovation (Hall and Soskice 2001). On the other hand, CMEs have labor market regimes characterized by continuous human capital investment in firms and relatively rigid hiring and firing systems, which have led to institutional settings more suitable for incremental innovation (Hall and Soskice 2001).

Workforce flexibility is a useful indicator of workers’ mobility and firms’ innovation outputs.

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Scholars have categorized firms’ human resource management into numerical flexibility and functional flexibility (Kleinknecht et al. 2014). Numerical flexibility refers to the ease for companies in placing skilled workforce to their needs, which is relevant to companies’ hiring and firing pattern and thus is easily observable in LMEs. On the other hand, functional flexibility indicates the degree to which employees are placed into multiple tasks through continuous upgrade in their skill sets (Backes-Gellner et al. 2016).

As such, functional flexibility is more conspicuous among CMEs. Recruitment of academic personnel and skilled workforce who can provide external knowledge is essential for companies’ radical innovation through increasing absorptive capacity. In general, this absorption of outside knowledge to create novel products requires numerical flexibility, which represents a feature of LME (Backes-Gellner et al. 2016).

The LME-specific institutional setting in the U.S. leads to firms’ more reliance on numerical flexibility due to the features of the decentralized wage-bargaining system and deregulated labor market and less employee protection. This is translated into relatively higher turnover rates, as hiring and firing becomes easier (Kleinknecht et al. 2014). Firms’ reliance on numeric flexibility is beneficial for radical innovation for two main reasons. First, it allows firms to engage in more entrepreneurial risks, since they could easily fire a part of their workforce in case of failure (Kleinknecht et al. 2014). A Flexible workforce is also conducive to greater inflow of “fresh blood,” talents with new ideas that drive radical innovation since the new entrants come with cutting-edge technologies and advance the existing knowledge in companies (Bauernschuster et al. 2008; Kleinknecht et al. 2014). The success in radical innovation in the U.S. can be accounted in part by numeric flexibility and thereby higher turnover that the existing LME labor market institution influences. This can be seen in the Silicon Valley recruitment culture where new ventures easily hire talents with general skills and let them go once the companies need new job requirements (Kleinknecht et al. 2014).

On the other hand, in Germany, the workforce gets continuous upgrading of knowledge and discretion in problems-solving—i.e. workplace relies more on functional flexibility and has low numeric flexibility since the country is focused much on vocational training in the workplace (Backes-Gellner et al. 2016). This has led to relatively lower turnover rates in Germany and yet has contributed to the country’s success in radical innovation (Bellmann et al. 2018). Why has low labor turnover generated high performance in radical innovation? In Germany, firms offer continuous training in firm-specific knowledge to make workers experiment with new technologies and thereby advance the firms’ knowledge base and subsequently result in radical inventions (Bauernschuster et al. 2008; Breznitz 2014). In fact, the disruptive technologies today such as automotive driving, sensory processing, digital communication require a combination of new ideas and the existing expertise (Grashof et al. 2019). Another comparative advantage of firms’ human resource management relying on functional flexibility is contributing to stronger social network among workforce (Bauernschuster et al. 2008). This suggests that comparatively rigid labor market regime in Germany does not necessarily hinder radical innovation. Instead, vocational training promotes radicality through collaboration among workers by integrating different abilities under stronger social ties within the organizations (Bauernschuster et al. 2008). Germany’s continuous vocational training provided to workers to develop firm-specific skills suggests how the CME-specific feature can stimulate radical innovation in a way distinct from LME.

Prominence of Innovation Clusters & Technology Transfers

The second indicator of radical innovation is the presence of innovation clusters in the countries.

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The concept of clusters was first introduced by Porter (1998), which refer to “geographic concentrations of interconnected companies and institutions in a particular field” (Porter 1998). Porter holds that clusters serve as a crucial determinant for national competitiveness since they enhance firms’ productiveness within the clusters through spurring innovation and establishment of new entrepreneurship, which reinforce the expansion of clusters and productivity growth therein. Clusters are conducive to firms’ innovation, as firms in the same industry are concentrated within the cluster and thereby benefit from sharing expertise and resources (Grashof et al. 2019). The vitality of clusters is indeed influenced much by national institutional settings such as government and universities/research institutes (Porter 1998; Sternberg et al. 2010).

Although the VoC framework does not touch upon the concept of geographic proximity in innovation, the facilitation of knowledge transfer within the regional clusters has spurred the production of patents, which is found to be evident in the number of high-tech clusters in the U.S. (Casper and Whitley 2004; Grashof et al. 2019). Another firm-level empirical study by Hinzmann, Cantner and Graf (2017) shows how German firms perceive that the spatial proximity between strategic partners is a crucial success factor for projects that deal with producing new, disruptive technologies in clusters. This gives ground to some extent to say that innovation clusters appear as a feature of LME given how high labor mobility that offers easy access to the talent pool, and how technology transfers on new technologies but also spur intense competition among firms in the clusters (Link et al. 2015; Sternberg et al. 2010).

The high-tech clusters in the U.S. developed with the help of its LME-specific institutional environment, flexibility in mobilizing the workforce, knowledge in the labor market through stimulating flexible adjustment to fast-moving markets and technologies (Sternberg et al. 2010). Although the private business sector mainly led cluster development in the U.S., the federal government as also contributed to the rise through a series of policies such as research funding by the National Science Foundation as to spur innovation and commercialization of new inventions (Sternberg et al. 2010). The initial development of Silicon Valley was due to flexible response to customer needs and learning new technology in companies within the cluster (Porter 1998). Flexibility in recruiting specialized workforce, reduced costs in market research, and active technology transfers within the clusters have been the basis for radicality in the Bay Area (Grashof et al. 2019). The fluid labor market regime and higher labor turnover, which is in line with the previous section, has led to relatively more competition-based clusters between different regions (Hall and Soskice 2001; Sternberg et al. 2010). Companies in innovation clusters are in intense competition to attract talents by providing stock options, adjustable working conditions, since retaining talent workforce is critical to innovation output in the high-tech sector (Ester and Mass 2016).

Germany has also developed innovation clusters, which the federal government mainly led.

The motivation for cluster policies is to catch up with the U.S. to commercialize new inventions in hightech industries and prioritize the formation of network structures through regional clusters for national innovation endeavor (Sternberg et al. 2010). The inception of nationwide cluster policy in 1995 brought the subsequent growth of biotechnology clusters, so-called “BioRegio”, enabling the growth of the bio/ medical technology sector in the cities of Munich and Regensburg (Segers 2016; Sternberg et al. 2010).

The key contributor to the rapid growth is ascribed to strategic partnership and collaboration among universities, research institutes and big pharmaceutical companies, which have helped innovative research output gets easily commercialized (Segers 2016).

The introduction of a new, comprehensive cluster initiative called “Leading-edge Cluster Competition” by the Federal Ministry of Education and Research from 2007 to 2017 has also increased

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innovation activity in many regional clusters among different high-tech sectors (Rothgang et al. 2017).

The 15 leading-edge innovation clusters, including sectors like bio/medical technology, transport, electronics, were selected after the three rounds of competition and obtained federal funding for research and development (R&D) (Rothgang et al. 2017). Similar to the BioRegio, the selected clusters have benefited from strong networking and knowledge transfer between research and industry in improving their competencies (Rothgang et al. 2017). The Ministry’s report stated that Munich showed its particular strength as a cluster in the biotechnology sector for producing new drugs and therapeutic concepts, and Stuttgart for its strength in the transport sector for producing technology related to autonomous driving and new charging system for electric vehicles (Federal Ministry of Education and Research 2015).

The recent empirical analysis, based on patents produced by Grashof et al. (2019) found that currently Munich and Stuttgart are the most radically innovative cities in Germany, and their success is attributed to the prominence of regional clusters. Successful companies like Bosch, Siemens, and Daimler are headquartered in these regions and many research institutes along with Fraunhofer Society, the largest applied science research organization in Europe, are also located (Grashof et al. 2019). The strong network between companies and Fraunhofer Society, which is in part supported by the federal government, has yielded vibrant knowledge transfers of novel ideas from the research institutes to small-medium companies and stimulated commercialization within the clusters (Breznitz 2014).

The expansion of vibrant regional clusters has significantly contributed to each country’s achievements in radical innovation. Table 2 lists the existing high-tech clusters with their specialization of certain fields of technology along with successful companies and notable universities based on their patent activities. In Germany, besides Munich and Stuttgart, Cologne has recently become an innovation cluster based on its patent activity in basic material chemistry, a field of radical innovation, according to the Global Innovation Index 2019. In the U.S. in addition to traditionally known high-tech clusters like the Bay Area and Boston, New York City area is another growing cluster specializing in pharmaceuticals (Global Innovation Index 2019).

This indicates that the formation and consolidation of innovation clusters with the extensive nexus between academia and businesses is a significant element to the growth of radical innovation in both Germany and the U.S. The development of clusters in Germany exemplifies Germany’s institutional adaptation of an LME feature of spatial proximity for technological breakthroughs. Germany is applying the LME feature to succeed in radical innovation. This height of high-tech clusters then becomes a shared characteristic that drives radical innovation in Germany and the U.S.

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Germany

United States

Region

Field of Tehcnology

Companies/ Universities

Cologne-Dusseldorf

Basic material Chemistry

Henkel

Stuttgart

Transport, Biotechnology

Daimler

Munich

Transport, Biotechnology, Electrical machinery, apparatus

BMW, Bosch, Siemens

Bay Area (San Jose/San Francisco), Los Angeles, San Diego

Computer technology, Digital telecommunications, Medical technology

Google, Qualcomm, University of California

Boston Cambridge

Transport, Biotechnology

MIT

New York City

Pharmaceuticals

Honeywell

Table 1: Top 3 Regional High-tech Innovation Clusters in Germany and United States Source: Grashof et al. 2019; Global Innovation Index 2019.1

Resilience of Startup Ecosystem

The discussion of high-tech clusters in the previous section leads to a more thorough examination of start-up companies’ resillience within the clusters. The role of start-up is salient to inventions of cuttingedge technology (Ester and Mass 2017; Lee et al. 2018). The innovation-friendly/risk-taking entrepreneurial culture has been noted for the enduring success of the Silicon Valley in high-tech sectors (Ester and Mass 2017). Indeed, the LME-related financial institution of short-term shareholder/venture capital is invested in high-risk, high-return projects in new ventures (Dilli et al. 2018). Since the inventions and adoption of disruptive technology generally require high risks, tolerating risks and sacrificing assets for higher returns in the future is necessary for radical innovation (Richter et al. 2018). An empirical analysis on the impact of firms’ risky behavior on radical innovation shows that tolerance of risks is a main driving force for radical innovation in converting patents to commercialized products in the marketplace (Tellis et al. 2009). This age of digital transformation has stimulated the establishment of start-ups, as they are the key producers of disruptive technology that are crucial for national competitiveness (Richter et al. 2018). This suggests that a robust start-up ecosystem characterized by easy access to venture capital funding, government’s support to start-ups can serve as an explanatory variable for a country’s notable performance in radical innovation. In this section, the attitudes toward entrepreneurial failure will be employed to show the degree of resilience of start-up ecosystem in each country. This is then followed by the discussion on venture capital investment as another indicator of the resilience of start-up environment.

1 In the U.S., the Research Triangle in North Carolina has been an eminent innovation cluster yet was excluded from this list because its patent activity was not strong compared to the three regions according to the Global Innovation Index.

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The corporate culture in the U.S., not just in the Silicon Valley, encourages companies to embrace risks to promote innovation and does not stigmatize failed entrepreneur (Richter et al. 2018), as figure 5 illustrates. The data is obtained from a report published by the World Economic Forum (Schwab 2018).

The result is based on response to a survey question, “In your country, to what extent do people have an appetite for entrepreneurial risk?” where score 1 is “not at all” and 7 is “to a great extent” (Schwab 2018).

The U.S. has long scored around 5 and 6, which is the highest among the seven countries from 2008 to 2015 but was caught up by Israel in 2016. This indicates that Americans are less aversive and more prone to take entrepreneurial risk than the other five countries. Indeed, students in the Bay Area are very ardent in creating their own start-up companies and universities even have courses related to management to support their students’ entrepreneurship (Ester and Mass 2017). Many start-ups in the Bay Area are showing strength in life sciences, AI and Robotics with their talent pool from Stanford University and UC Berkeley (Startup Genome 2019). The Kendall Square near MIT in Boston also has high a concentration of startups created by students, where the city specializes in biotechnology and robotics (Karagianis 2015).

New York City, a growing high-tech cluster as the previous section noted, is also a global hub for startups specializing in life sciences and AI/Big Data (Startup Genome 2019).

In Germany, corporate culture has long been disadvantageous to start a new business since people are more risk-averse and concerned with stigma from failure (Fuerlinger et al. 2015; Richter et al. 2018).

Despite the federal government’s attempts to foster the creation of startups in high-tech industries, the rate of establishing new entrepreneurship has been lower than that of the U.S. (Richter et al. 2018). However, Figure 5 shows that Germany has recently been improving in building new business startups. The score was initially the lowest, around 2 and 3, among the six countries but it started to increase in 2013 and peaked after the U.S. and Israel in 2018. This indicates that over the last seven years Germans’ have become more willing to take entrepreneurial risks over the last seven years. According to the Global Startup Ecosystem

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Report 2019, Berlin is currently ranked the 10th in the global start-up ecosystems and Munich just entered as a new growing hub for start-ups (Startup Genome 2019). Berlin has a strong startup ecosystem in life sciences and the fintech sector—blockchain technology, and startups in Munich show strength in bio/ medical technology (Fernandez 2018; Startup Genome 2019). Berlin and Munich are the top two cities in Germany having the most start-up companies germane to AI and the three most popular areas within AI are transport, life sciences and pharmaceuticals, and manufacturing (“AI Startup Landscape 2019”).

LME’s comparative institutional advantage for establishing new entrepreneurship is also based on access to venture capital, which is a financing institution that decides shareholders’ propensity to make investments in new ventures (Dilli et al. 2018). In contrast, firms in CMEs tend to rely on comparatively less risky and long-term capital investment (Hall and Soskice 2001). Since venture capital is a significant financial source for new high-tech companies as it tends to overlook the companies’ failures (Hall and Soskice 2001), the vitality of venture capital investment activity can therefore serve as another measurement for the resilience of start-up ecosystem. Access to venture capital has long been restricted in Germany compared to the U.S. The reason for this is that companies in CMEs offer greater protection for employees as a way cultivate asset-specific skills, which make them engage in less risky investment (Dilli et al. 2018).

However, Germany’s venture capital market has been growing recently. In order to provide a conducive environment for venture capital, the German federal government introduced the investment grant for venture capital in 2013 called “INVEST,” which provided 20 percent subsidy for business “angels” investing in new high-tech firms (Federal Ministry of Economy and Energy n.d.). In the same year, more than 250 million Euros were invested in 262 IT start-ups in Germany (Fuerlinger et al. 2015). As of December 2018, 65 percent of the investment went to the ICT sectors (Federal Ministry of Economy and Energy n.d.) In 2018, Germany was ranked eighth—the U.S. the first—in the Venture Capital & Private Equity Country Attractiveness Index from IESE Business School. In this index, Germany exhibits strength in entrepreneur opportunities, including costs/number of procedures/times needed to start a business, corporate R&D, etc. (Groh et al. 2018). This result is notable, given Germany’s score on entrepreneur culture and deal opportunities is ranked the second after the United Kingdom in Western Europe (Groh et al. 2018).

German start-up ecosystem is less mature than the U.S. in entrepreneurship concerning the number, diversity, and valuation of the startups (“Startup Genome” 2019). Nonetheless, the German government’s enduring support through funding and scholarship for entrepreneurship and gradual change in Germans’ perception toward business failure has helped new start-ups make inroads to performance in radical innovation. The governmental policies and the rising number of start-ups in Germany suggest the country’s adjustment to this changing global economic circumstance governed by digital transformation, where expediting start-ups is an important strategy to gain competitiveness in disruptive technologies and thereby economic productivity (Lee et al. 2018). These findings on start-up ecosystem in Germany show that the country has an environment for entrepreneurship that is becoming resilient, given the improving perception towards entrepreneur risks and increasing venture capital. This illustrates the country’s growing competitiveness in radical innovation. This, in turn, shows that existing LME-CME dichotomy does not have a decisive explanatory role in national innovation output. Rather, Germany’s recent adaption of a conducive environment to venture capital growth which is in line with the increased appetite for entrepreneur risk taking represents the country’s institutional hybridization for radical innovation.

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Conclusion Region

Germany

United States

Labor Market Regimes: Workforce Flexibility

CME • Reliance on functional flexibility–continuous vocational training • Low labor turnover rates

LME • Reliance on numeric flexibility • High labor turnover rates

Innovation Clusters & Technology Transfers

LME-specific feature: Existence of vibrant high-tech clusters and knowledge transfers between academia and the business sector

Start-ups Ecosystem

LME-specific feature: Resilient start-up ecosystems in both countries–relatively mature in the U.S. and incipient in Germany • Improving attitudes towards entrepreneur risks • Increasing venture capital invesment

Table 2: Contributors to Radical Innovation

This study argues that Germany, based on its patent counts, has gained its competitiveness in radical innovation over the past seven years due to the institutional hybridization—retaining CME-specific feature of workplace vocational training and adopting LME-specific features such as innovation clusters and start-up ecosystem. Table 2 summarizes how each domestic institution plays a principal role in shaping Germany’s strength in radical innovation. This finding challenges the VoC approach, which characterizes CMEs has laggards in radical innovation. This does not necessarily disregard the merits of the VoC approach, since according to the above investigation, there are still distinct institutional features between two countries distinguished by the framework, workforce flexibility. In sum, Germany’s competitiveness resides in its institutional hybridization of combining certain CME features with LMEs ones. Germany’s adaptation of its traditional political-economic institutional arrangement has created an environment conducive to entrepreneurship development and radical innovation.

The long-standing tradition of comparatively fluid labor market system in the U.S. has allowed companies to emphasize on numerical flexibility for frequent influx of talents with fresh ideas for radicality.

This higher labor mobility follows companies’ fierce competition to recruit talented workforce within and between innovation clusters and also more propitious environment for entrepreneurship (Ebner 2010; Sternberg et al. 2010). On the other hand, Germany has succeeded in radical innovation despite its more rigid labor market structure, where the workforce is less mobile, and companies devote to continuous vocational training. This is because continuous vocational training allows German workers to upgrade their knowledge that is later applied to create new technological breakthroughs. Germany shows its institutional adaptation in developing high-tech clusters under the federal government’s leadership, which are now vibrant sources of radical innovation. Compared to the very mature start-up ecosystem in the U.S., the German start-up environment is comparatively embryonic yet is growing apace, which serves another institutional adaptation from LME. In turn, the prominent innovation clusters and resilient start-

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up ecosystem became the shared institutional features between the U.S. and Germany.

Ornston (2012) classifies the Nordic CMEs as creative corporatist states, where the combination of traditional corporatism such as inter-firm relations and newly introduced market institutions such as early-stage risk capital go hand in hand for radical innovation. Ornston’s study suggests that Germany could also be a case of an institutional adaptation, as the federal government promotes high-tech clusters and entrepreneurship on purpose to succeed in radical innovation. In fact, this institutional hybridization indicates how countries, not merely limited to Germany and the U.S., convergently response to the PostFordist production system in this era of digital transformation. This revolutionary phase of industrial production governed by disruptive technologies like AI, 5G, internet of things, rests heavily on the existence of an institutional setting propitious to radical innovation. This, in turn, also aligns with Baccaro and Howell (2011) that institutional convergence occurs through “reengineering of existing institutional sets” to produce a similar outcome of success in the high-tech sectors (526). Given the growing importance of the role of entrepreneurship in bringing novelty in the marketplace for national competitiveness (Lee et al. 2018), Germany’s hybrid innovation model suggests an inevitable adaptation to adjust to a fast-moving global economic paradigm. Through the lens of national innovation models in Germany and the U.S., this study asserts that Germany has adapted some of its political-economic institutions to exploit radical innovation opportunities in the current digital era.

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Is Citizenship a Derivative of Anti-Blackness?

Kenya Moore

This paper aims to analyze the origins and functionality of citizenship as with early settler colonial legal doctrine established

by European settler states. Building upon the history and development of the nation and the subsequent need for contemporary citizenship, this paper aims to fully articulate the correlation between citizenship and anti-Blackness. In examining citizenship and nationality law as it was intended to function, it is useful to do so through the gaze of decolonization. A facet of decolonization is examining the foundations on which settler colonial states exist and have been allowed to exist based on the premise of democracy. The existence of the state and one’s relationship to the state are necessary conversations in understanding the trends and use of citizenship as a political and social tool. For this reason, I will focus on analyzing social historical arcs, as well as relevant legal doctrine and jurisprudence in relation to the origin and function of citizenry.

it has evolved, beginning

This paper mostly, though not exclusively, focuses on the evolution of citizenry in the West. It is also important to note that the development and evolution of citizenship in the East is more heavily associated with citizenship education, more so than other variations of civil, political, labor, and ownership related origins of citizenry. Furthermore, Western implications of citizenship are more apparently linked to the establishment of the nation and statehood.

As one reads this paper the following terminology are theorized and should be understood as follows: Citizenship The word “citizenship” has European roots, but the question of political belonging has been one of general inquiry that transcends various identities.2 This is evident when we prompt ourselves to examine the conceptual meaning of the citizen and citizenship in relation to the ways in which we think about political belonging in other parts of the world. The comparative perspective broadens the scope of inquiry. However, it only takes us so far, “for at a certain point, with the deployment of European power across the world,” 2 Frederick Cooper. Citizenship, Inequality, and Difference: Historical Perspectives. Princeton: Princeton University Press, 2018. ProQuest Ebook Central, 32

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different political structures came to be inequitable with one another, and the “language of citizenship became a terrain in which claims and counterclaims were made within European empires and within other imperial regimes.”3 As movements in differing political and cultural contexts “invoked citizenship,” it acquired several new meanings.4 Citizenship takes on various forms and definitions in various contexts. Specific forms are constituted in and through “distinct political projects and cultural formations.”5 Thus, confining the concept of citizenship to rigid definitions and political essentialism would be an oversimplification, as that would decontextualize its usage. Throughout the paper I will situate the concept in its circumstantial relevance. By doing so we are able to critically engage with the evolution of belonging in the post-colonial world.

Anti-Blackness and Indigeneity In exploring the relationship between citizenship and anti-Blackness, antiBlackness must not be defined to be synonymous to overt racism, but rather a structural and systemic discrimination based on notions of inferiority and primitivity that consequently affects those in proximity to Blackness more than those that sit in closer proximity to whiteness. It is experienced in various degrees at the intersections of race, class, gender, sexuality, and language.6 Indigeneity is intrinsically linked to understanding how anti-Blackness is situated in the structural legacies of colonialism, as they were simultaneously conceptualized through binary modes of euro-centric logic, characterized by racialization and colonization.7 This necessitates the Indigenous experience and identifier to be defined broadly, as to include “Indigenous, the Native Americas, Australian, Hawaiian, Caribbean, and African conceptions.”8 In establishing Indigeneity as an international category, “we stake different positionalities,” in the communal investment and critique of Euro-global modernity and decolonization.9 Concerned with the ways in which contemporary 3 Frederick Cooper, supra note 1.

4 Ibid.

5 John Clark, Kathleen Coll, Evelina Dagnino, and Catherine Neveu. Disputing citizenship. Bristol: Policy Press, 2014.

ProQuest Ebook Central., 12 6 George J. Sefa Dei. Reframing Blackness and Black Solidarities Through Anti-Colonial and Decolonial Prisms.

Cham: Springer International Publishing AG, 2017. ProQuest Ebook Central, 101 7 Ibid.

8 Id. at 70.

9 Id. at 101.

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Racialization, Ethnicity, and National Boundaries

As the connections between citizenship and anti-Blackness become increasingly evident, it’s important that scrutinize the social constructions on which the foundations of our social reality and fact are built upon, beginning with race and identity as identifiers. The idea of race became an “essential feature of early societal formations as white explorers searched for social explanations and answers about the nature and consequences of human differences in everyday social relations,”12 especially in the matter of the allocation of social services and goods. Race and racism are historically encoded in white European power and belief systems.13 Race anthropology asserts that the “origins of the race concept must be appropriately tied to Western European philosophical and belief systems,”14 and more distinctly, to “colonial and imperial expansion activities” effectuated by Western powers and “economic capital” throughout the seventeenth century.15 Race, since the time of its inception, was and continues to be a powerful and useful concept for grouping together human variation observed through the European explorers, conquerors, and colonizers gaze.

Unlike race, which is predominately, and in part, defined by physical attributes, ethnicity is socially defined by a collective cultural identity.16 Colonialism, although having not invented ethnicity, utilized the pre-colonial system of categorization as a colonial administrative instrument.17 What were flexible forms of identity were rendered more rigid and politically relevant, especially with regards to border formation.

The changes colonialism cultivated in terms of how nature was conceptualized are distinctly linked to group membership. In general, “nature was understood in pre-colonial Africa as an open space, usually differentiated into known and named water and land resources and sacred sites.”18 With the emergency of colonialism, nature became demarcated as “‘territory’, divided by international, regional and ethnic 10 George J. Sefa Dei, supra note 9, at 70.

11 Ibid.

12 Ibid.

13 Ibid.

14 Id. at 72.

15 Id. at 70.

16 Stephen Spencer. Race and Ethnicity: Culture, Identity and Representation. London: Taylor & Francis Group, 2014. ProQuest Ebook Central., 19 17 Morten Bøås and Kevin C. Dunn. Politics of Origin in Africa: Autochthony, Citizenship and Conflict. London: Zed Books, 2013. ProQuest Ebook Central., 17 18 Ibid.

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borders.”19 Space and spatiality became “‘tamed’, fixed and stabilized; an ‘immobile closed system.’”20 The formation of territory, national boundaries, and nation-states then roots itself in claims to sovereignty, meaning power, and reify center-periphery politics, as well as the gestation of belonging.21 This is pertinent to the configuration and execution of settler colonialism and settler-hood.

Within colonial histories settler-hood must be read in the context of specific colonial histories.

The term denotes “occupation on stolen lands through acts of violence, land dispossession, displacement of original/Indigenous inhabitants, genocide, and theft.”22 The settler sustains the legacy of settler-hood by assuming “legitimate entitlements” to the land and by creating legal and governing systems and structures that become fundamentally linked to the territory, further legitimizing colonial settler occupation.23

The dispossession of Indigenous peoples who become separated from their land, as well as their indigeneity, subsequently renders them as invisible given that as the colonial settlement evolves, identity becomes inherently linked with territory.24 The settlers’ then assumed entitlement to the land “estranges Indigenous people strangers from their land, their nationhood, their leaders, their communities, their families and themselves.”25 Land dispossession “deeply and abrasively eviscerates the material and psychocultural worlds of Indigenous peoples [everywhere,] in an effort to immobilize whole societies.”26 This violence is then “recapitulated over and over again through legal statutes that transfer property and rights to colonial occupiers.”27 By taking possession of and occupying Indigenous land under no legal merit, the settlers’ claim to land ownership is used to maintain, enhance, and assert their power over others.

The “colonial occupier/settler” does this by “(over)determining, and entrenching this overdetermination in laws and government.”28 Through these laws and governing structures that become increasingly refined with each phase and evolution of colonialism, the settler is repeatedly reconstituted.29 The recreation and construction of this social order and reality alongside the distribution of power gives political significance to racial identity, thus constructing whiteness.30

Whiteness is delineated by social and political power maintained through law and governance that derived from the colonial system; And sequentially established determiners for who enters and “(eventually) inhabits the colonial nation and who does not; who becomes a citizen and for how long, and who does not; who has access to valued goods and services and who does not; who has a home and who does not; who 19 Morten Bøås and Kevin C. Dunn, supra note 17.

20 Ibid.

21 George J. Sefa Dei, 72 22 Ibid.

23 Ibid.

24 Ibid.

25 Ibid.

26 Ibid.

27 Id. at 89.

28 Ibid.

29 Ibid.

30 Teresa J. Guess. “The Social Construction of Whiteness: Racism by Intent, Racism by Consequence.” Critical Sociology 32, no. 4, Koninklijke Brill NV, Leiden, 2006. SAGE Journals., 13

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can engage in and benefit from resource extraction and who cannot; who lives and who does not,”31 who belongs in and outside the context of territorial boundaries, and who does not.

This secures and enhances privileges of determinate agency through repetition, and depends on the absence of and/or “uneven respect” for the rights of non-settlers through time, in this case non-settlers meaning those who do not have access to and mobility through whiteness.32

Modernity of the Nation and Citizenship: The Origin

Using the historical arc of late fifteenth century settler colonialism as a frame of reference, we move into an era characterized by modernity in the mid-eighteenth century. During this time frame notions of nationhood and citizenship are more concretely established, marked, and documented through legal doctrine by major colonial powers. This brings our attention to the French Revolution as a site of origin in citizenry.

This era can be characterized by: “The delimitation of the citizenry; the establishment of civil equality, entailing shared rights and shared obligations; the institutionalization of political rights; the legal rationalization and ideological accentuation of the distinction between citizens and foreigners; the articulation of the doctrine of national sovereignty and of the link between citizenship and nationhood; the substitution of immediate, direct relations between the citizen and the State for the mediated, indirect relations characteristic of the ancien régime.”33

The Revolution brought all these developments together on a national level for the first time.34 This model of national citizenship is said to have served as an “image of its own future,” for both France and the rest of the world.35 This historical arc invented both the “nation-state and the modern institution and ideology of national citizenship.”36 The invention of the nation-state presupposed centuries of statebuilding and the slow growth of “national consciousness within the frame of the developing territorial state,” as did the invention of the modern institution of national citizenship which was built on the theory and practice of “state-membership in the ancien régime.”

Ancien-régime society in France can be understood as one that was inegalitarian in nature.37 It was a society characterized by rigid political and social system, divided into three disproportionate and unequally treated classes. Embedded with notions of privilege “…enjoyed by certain [persons] and denied to other,” the societal foundation from which we derived contemporary citizenship was intentionally

31 George J. Sefa Dei, 93 32 Ibid.

33 Rogers Brubaker, Citizenship and Nationhood in France and Germany. Cambridge: Harvard University Press, 1992. ProQuest Ebook Central, 35 34 Ibid.

35 Id. at 36.

36 Ibid.

37 Id. at 35.

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constructed on the basis of inequality.38 At this time France linked class with race.39 Legal inequality, not to be conflated with simple factual inequality, was the basis of the social order.40

Citizenship was not an independent branch of the law in the ancien régime, nor was it defined independently of the rights that, in theory, were contingent upon its status.41 Instead of inheritance rights, or any other rights, depending on an independently defined citizenship, the definition of citizenship “depended on beliefs about who ought to be able to inherit.”42 Thus, a person claiming an inheritance from their parents had a better chance of being considered a citizen as opposed to a person claiming an inheritance from a more distant relative, even under the conditions that the two were identically situated with respect to birthplace, parental citizenship, and domicile.43

Given that citizenship was not “consistently defined or systematically codified,” It was determined in an ad hoc manner in order to make it coincide with legal judgments about inheritance rights. The Revolution was to change all this. After 1750, France concluded treaties with most European States, each State reciprocally exempting citizens of the other from the droit d’aubaine, the right of the king to inherit property of deceased foreigners.44 By the late eighteenth century only a small fraction of foreigners remained subject to the droit d’aubaine.45 Although French law did not “systematically discriminate against foreigners,” per se, on the cusp of the Revolution, the “correlative statuses of French citizen and foreigner” existed in an embryonic form.46

In the feudal period the foreigner or, the aubain, was defined in reference to the seigneurie (the land), not with respect to the kingdom: as he was the person born “outside the seigneurie.”47 And the droit d’aubaine belonged to the seigneur, not the king. Between the late thirteenth and fifteenth centuries, however, the king redefined the aubain as the person born “outside the kingdom,” and in seizing the seigneurial droit d’aubaine, the inheritance of the land of the outsider.48 Concomitantly the king effectively monopolized the right of “naturalizing” foreigners. This created for the first time a kingdom-wide status of foreigner and, correlatively, an embryonic legal status of French citizen or national.49 However, these statuses were not clearly defined. The legal distinction between French citizen and foreigner thus originated in the late medieval consolidation of royal authority at the expense of “seigneurial rights,” land rights.50

Reflected in the fabric of contemporary citizenship doctrine, every State claiming sovereignty 38 Rogers Brubaker, supra note 37, at 36.

39 Ibid.

40 Rogers Brubaker, 45 41 Ibid.

42 Ibid.

43 Id. at 38.

44 Id. at 37 45 Ibid.

46 Ibid.

47 Id. at 46.

48 Ibid.

49 Id. at 50.

50 Ibid.

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has its own nationality law and divides the world accordingly into citizens and foreigners.51 This formal legislative “delimitation” of the citizenry was unknown in the “territorial states” of medieval and early modern Europe.52 Citizenship remained incipient as the other was becoming more concrete. This is not to say that there weren’t any rules determining who was and was not a “citizen” in early modern France.53 While there weren’t codified, enacted rules, there were customary rules, “supplemented by a growing body of jurisprudence.”54 Since foreigners’ rights to bequeath or inherit property were limited, the qualité de français mattered, a term coined to mean French nationality.55 When this was contested in the course of an “inheritance-related dispute,” the parliaments, which at the time were supreme judicial bodies rather than legislative, were called upon to settle the issue.56 In doing so, they did not define the “criteria of citizenship” in general terms, but determined citizenship status in specific cases.57 Legal commentators and scholars have extracted general rules from an analysis of these particular cases.58 These rules, nonetheless, would be more accurately characterized as “tendencies,” as reflected in the decisions of different parliaments, even those of the same parliament, were not always consistent.59

This evolution was not driven by a changing “conception of nationhood or citizenship,” as whether or not one was of French birth was incidental in this jurisprudence; the real issue was the question of inheritance.60 The move towards more inclusive criteria of citizenship seemingly results from a concern that persons domiciled in France not be “arbitrarily deprived of an inheritance” because they had been born abroad, or born to foreign parents.61 Equity within this social context required that persons with a substantial connection to France be able to inherit. Since the parliaments were not legislatures, they didn’t have the ability to change the law of inheritance, which discriminated against foreigners. They could, however, construct the qualité de français (french nationality) in a more expansive manner.62

Legal Doctrine of the Revolution

French Declaration of the Rights of the Man and of the Citizen (1789)

On August 26th, 1789, the French National Constituent Assembly issued the Déclaration des droits de l'homme et du citizen, also known as the Declaration of the Rights of Man and the Citizen.63 51 Rogers Brubaker, supra note 50, at 47.

52 Ibid.

53 Ibid.

54 Id. at 87.

55 Id. at 46.

56 Ibid.

57 Ibid.

58 Ibid.

59 Id. at 87.

60 Id. at 89.

61 Ibid.

62 Id. at 46.

63 “The Declaration of the Rights of Man and of the Citizen.” The British Library. The British Library, December 2, 2014.

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This document formally defined individual and collective rights in the latter years of French Revolution.

Admirable of the consumable construction and certain aspects of the Magna Carta, an English charter that concisely articulated the relationship between the subject and law, the Déclaration rejected appeals to ancient charters of liberties based on the principle that the rights of man were “natural, universal and inalienable.”64 The enumerated rights of the citizen rendered the monarchy subordinate, subsequently refining French nationality by way of how citizenry should take shape through individual rights and privileges.65

Notably, the Déclaration did not revoke the institution of slavery. Black people were excluded from both the theory and the construction of citizenship just as they were excluded from the construction of civilization, made evident throughout the evolution and stages of both colonialism and settled colonialism that necessitated their enslavement.

Modernity of the Nation and Citizenship: Contextualizing Anti-Blackness

The Spanish Empire

As we move into the nineteenth century, this time period becomes known as the age of revolution.

Between 1810 and 1812, as rebellions in various of the Americas uprise, American and Iberian leaders converged on the Spanish city of Cádiz to try to hammer out a constitutional compromise.

The attempt to devise a constitution for this complex political entity ran into conflicts of interest between Peninsular and American Spaniards, in addition to conflict over different notions of belonging.66 The Cádiz constitution of 1812, after various compromises embraced a singular Spanish nation on both sides of the Atlantic.67 It defined Spaniards as “all free men born and domiciled in Spanish domains and their children, all foreigners with naturalization letters, all foreigners who, without such letters, were citizens of local communities for at least ten years, and all freemen who obtained their liberty in Spain.”68 Spanish America was included on the same basis as any other Castilian territory, and Indigenous people were included alongside people whose roots were in European Spain.69

From Cádiz emerged a constitutional monarchy, with elections at different levels. The constitution has had long-term, lasting impacts. Establishing a citizenry with relation to elections, what was then, and often now, the “ultimate arbiter of political legitimacy.”70 Most countries followed a less linear path toward an inclusive electoral system, described as being a “zig-zag.”71 This new political order was characterized as revolutionary: “For the first time and at one stroke, hundreds of thousands of Spaniards in the peninsula and across the empire were called to vote and participate in the political process.”72 The Cádiz constitution 64 The British Library, supra note 63.

65 Ibid.

66 Frederick Cooper, 43 67 Ibid.

68 Ibid.

69 Id. at 41.

70 Id. at 43.

71 Ibid.

72 Id. at 42.

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abolished seigneurial structures, Indigenous tribute, and forced labor imposed on Indigenous people (including the system that had been the basis of silver mining).73 It “vested sovereignty in the nation,” not in the king, although it did give the monarch the task of implementing the laws.74 Here we see the delineation of a constitutional monarchy on an massive imperial scale.

The word ‘citizen’ gains a radically new meaning during this era. The citizen is no longer simply the inhabitant, it is the member of the nation, which at the time was a developing concept that now “designates the collective entity formed by all the citizens and sole depositary of sovereignty within the State.”75 The word citizen thus from now on “condenses in itself two distinct but inseparable conceptual meanings: it designates the national of the country and the bearer of civic rights as if they are one and the same person.”76

At this time it was important to recognize Indigenous people as citizens based on the sole purpose of reinforcing the authority of the empire over all its lands and peoples.”77 However this logic did not apply to Africans and their descendants.78 Similarly to the French Declaration of the Rights of the Man and of the Citizen, the constitution did nothing to bring about the end of slavery. Even those who were of mixed African descent and would therefore be considered Spanish, were not considered citizens.79 They weren’t afforded any political rights. Africans, unlike Indigenous people, were assumed to be from an imagined “somewhere else.”80 The exclusion of Black people from citizenship did not reflect a consensus, but rather emerged out of intense debates and concerns about the “interests of slave owners, the dangers of slave rebellion, the participation of enslaved and former enslaved people on both sides of the independence struggles, and the worries of Iberian Spaniards that too inclusive a version of citizenship would overwhelm their numbers in representative institutions”81 The assumed predisposition undermined the unique social reality and death experienced by Black people; And thus, it assumes that the ways in which Blackness would express itself politically and socially is in inherent juxtaposition to the interests of a relationship between citizenship and the nation.

The inclusion of Indigenous people brought into the domain of citizenship people who were “culturally unfamiliar, of uncertain loyalty—and numerous.”82 The issue of representation was crucial to the Spanish empire, and it was fought over intensely within the Cortes.83 If Spanish sovereignty was unitary, but the composition of the nation was plural, then the weight given to each part of the whole 73 Frederick Cooper, supra note 72.

74 Ibid.

75 John Clarke, et al, 17.

76 Ibid.

77 Frederick Cooper, 42 78 Ibid.

79 Ibid.

80 Id. at 44.

81 Ibid.

82 Ibid.

83 Ibid.

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would naturally affect decisions covering the entire empire.84 If one followed the “logic of citizenship” and counted each individual, the question of should the “‘true’” Spanish people of Iberia be outnumbered by people of different racial categories from the Americas, whose relationships to each other and to Spain were unclear is begged.85 In contemplating this there was no consensus in the Cortes on how to balance the recognized components of the Spanish nation; this was a basic problem of “‘imperial constitutions,” in the Spanish Empire, in revolutionary France, as well as in the United States.86

Mediating citizenship status through local communities as a tactical control of access provided means for making distinctions. Jurists were careful to insure that land rights did not attach to the communities to which Indigenous people belonged, so as long as settlers were interested in those lands.87 So the structures of inequality, certainly of dispossession, were inscribed within a system that was incorporating much of the Indigenous population as “vassals of the king, as potential converts, and as members of a hierarchy of communities with the kingdoms of Spain at the top.”88 Brining to the forefront the ways that indigeneity, land, and settler colonialism find mobility in the conceptualization of a legal belonging. This is evident of how visceral the legacies of colonialism were coming to be. In places where Spanish officials could claim that Indigenous people had failed to “improve” their land for agriculture, the appropriation of that land could then be justified.89 Where Indigenous people resisted the power of the crown, there was all the more reason to dispossess them.90 We’re then forced to critically consider the convoluted positionality of Indigenous people in the Spanish empire. Although they were not right-less, their rights were conditional.

It is at this point that we see the nascent ways in which citizenship are rendered to be restrictively inclusive of non-Black, non-white people and contingent upon docility. The experience of Black people in the Spanish empire was of a distinctive legal and social exclusion, whilst Indigenous people (who are in closer proximity to Blackness than they are to whiteness) experienced a conditional legal and social status that was evidently exclusionary as well, in part. Indigenous people in this society were not able to fully realize the same rights as white people, just the illusion. This is illustrative of the spectrum on which anti-Blackness is both experienced and articulated in and outside of law.

The British Empire

The English revolutions of the seventeenth century brought forth a notion of parliamentary government based on a restrictive, property-based franchise.91 Its postulated that the roots of citizenship in Britain are found in “the evolution of its judicial system, including the notion of trial by jury.”92 The notion of “the freeborn Englishman” carried weight in the eighteenth century, it created a strong

84 Frederick Cooper, supra note 83, at 53.

85 Id. at 58.

86 Id. at 55.

87 Id. at 58.

88 Ibid.

89 Id. at 59.

90 Ibid.

91 Id. at 47.

92 Ibid.

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notion of belonging, which asks us to consider who was entitled to “political voice.”93 In this context of disillusionment over political rights in “the space of empire,” demands for a distinct citizenship in British North America turned into a revolutionary movement.94 Despite having been the largest modern colonial empire, citizenship as such was not concretely defined until the Nationality Act of 1948, which legally set forth citizenship of the “United Kingdom and Colonies” (inclusive of all inhabitants of the “dominions, colonies, and metropole” who had long been subjects of the king or queen).95

Prior to the Nationality Act of 1948, negotiations about whether the thirteen colonies would produce thirteen nation-states, each with its own citizens, or a single, federal state created significant discourse.96 The vigorous debate over this issue took place among leaders who were well aware that they lived in a world made up of empires, and that the danger of recolonization by the British or another colonial empire influenced the ultimate decision to create the United States, and with it, an American citizenry.97 Citizenship would also have to be defined against those Indigenous in the United States, for reasons similar to those laid out to justify the denial of citizenship to enslaved and formerly people in the Spanish empire.98 Once the colonies did unite and push westward, the United States defined Indigenous peoples as distinct “nations” whose separation and subordination were articulated in increasingly harsh ways.99 Even after the Civil War, the Fourteenth Amendment left “Indians not taxed” out of its “rights-bearing” horizon.100 To become citizens, Indigenous people had to cease to be Indigenous by way of assimilating to the dominant culture, in contrast to the provisions of the Spanish constitution of 1812. Only in 1924 did the Indigenous population of the United States acquire the status and enumerated rights of the citizen.101

Across the rest of the British Empire, the question of “what kind of polity people belonged to” remained a complex ideation.102 As Canada, Australia, and other dominions became “increasingly autonomous” over the nineteenth century, many of their leaders continued to see themselves as part of a British world “united by a supposedly common heritage and by whiteness.”103 In the late nineteenth and early twentieth century, the idea of a “Greater Britain” spread across the world and held significant meaning in imperial circles.

Just as we saw in the early articulation and origins of nationality law and citizenship in France and the Spanish Empire, the legal discourse with regards to enslaved people in the British Empire oriented itself in exclusion through the Civil War (1861).104 Enslaved people were excluded from citizenship, and formerly enslaved people were for the most part either “excluded or marginalized from mainstream society 93 Frederick Cooper, supra note 92.

94 Id. at 48.

95 Ibid.

96 Id. at 50.

97 Ibid.

98 Ibid.

99 Id. at 52.

100 Ibid.

101 Ibid.

102 Id. at 63.

103 Id. at 64.

104 Id. at 67.

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and politics.”105 Some slowly began to develop an African American sense of nation.106

U.S. Reconstruction and Incremental Citizenship

In 1863, following the Civil War, the Emancipation Proclamation began an incremental process to free African Americans in rebel states. Under federal law, the Thirteenth Amendment emancipated all U.S. slaves. This would be fully realized over the course of twelve years.107 The Reconstruction era, which lasted from 1866 to 1877, was a defining moment characterized by the construction of how whites and Blacks could live together in a non-slave society.108 After the Civil War, the ratification of the Thirteenth (1865), Fourteenth (1868), and Fifteenth Amendments 1870) to the Constitution, as well as the Civil Rights Act of 1866 extended the breadth of rights associated with U.S. citizenship to Black people.109 Under the law, Black people now had the right vote, actively participate in the political process, acquire the land of former owners, seek their own employment, and use public accommodations.110 However, the semblance of citizenship was eroded by state sanctioned violence and social policy. Specifically, The Black Codes and Jim Crow Laws. As U.S. state and local law, the limitations these doctrines imposed on Black citizenry and mobility rendered Black citizenship a communal praxis rather than an undisputed claim to innate rights within the territorial boundaries of the nation that whiteness is granted. It’s clear then that citizenship and anti-Blackness are intrinsically linked and globally exported from colonial powers to the settler states, in this example from the British Empire to the United States.

Conclusion

The post-Revolutionary shift and construction of citizenship is a critical starting point for understanding the intended nature of citizenship excavated from the State’s relationship to Blackness.111 Throughout this paper its clear that citizenship is, in part, a derivative of anti-Blackness. In the discourse of the origins of nationality law Black people were knowingly left out of these codified formations of citizenship. The origins of citizenry necessitated an other, a foreign, a standard on which citizenship gained its meaning in contrast to what did not denote such a social and political status. Numerous historical arcs have exemplified how in instances when Black and Indigenous people were afforded access to citizenship, the concept was reshaped to be conditional, allowing the post-colonial State to maintain power over communities should it be deemed justifiable through State interest. The question of Black citizenship draws 105 Frederick Cooper, supra note 104.

106 Ibid.

107 Nast, Thomas, Alfred R. Waud, Henry L. Stephens, James E. Taylor, J. Hoover, George F. Crane, and Elizabeth White. “The African American Odyssey: A Quest for Full Citizenship Reconstruction and Its Aftermath.”

Reconstruction and Its Aftermath - The African American Odyssey: A Quest for Full Citizenship | Exhibitions (Library of Congress). Library of Congress, February 9, 1998 108 Ibid.

109 Ibid.

110 Ibid.

111 Carter, Brittany. "Creating Black Citizenship: The Struggle Over Blackness in the Body Politic." Order No. 10139678, New York University, 2016. In PROQUESTMS Dissertations & Theses @ New York University; ProQuest Dissertations & Theses Global, 4

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our attention to the unique relationship between Black/African peoples and the nation-state, as well as the negotiation processes in which Black people engage in order to navigate national belonging.112

In white settler societies, “rights, privileges and social relations may be organized in such a way as to justify and legitimate discrimination” against anyone who is or can be defined as an outsider, including citizens.113 African/Black people are construed as outsiders in Western contexts, regardless of citizenship status.114

Reflecting on Citzenship in Modernity

The nation and citizenship appear to have always been intertwined, necessitated by one another through colonial values.115 In most cases, the nation-states have been and are the agents that inscribe, guarantee and police citizenship as a status.116 It is predominantly through States that “rights can be legally inscribed and implemented,” although various institutional sites, such as international and local governing bodies, tend to be endued with similar prerogatives.117 As a consequence, legal apparatuses become sites where citizenship can be “grasped as a political, juridical and administrative, but also cultural and social, category that distinguishes different types of subject […] and distributes rights and responsibilities ([i.e.], voting, protection under the law, social or welfare entitlements, etc},” without a fastidious correspondence between types of subjects and rights or responsibilities “(the latter might be accessible to different types of subjects at different times and in different places).”118 As an exported ideation that, as previously stated, takes various forms and definitions, citizenship is and will never be definitive, or universal in application.

Which is why there’s value in critically engaging with the rich textuality, historical development, and social fact of citizenry.

Citizenship is a “universal and distinctive feature” of the modern political landscape.119 Every modern State formally defines its citizenry, publicly identifying a set of persons as its members and residually designating all others as non-citizens, or, as more commonly referred to in early citizenship text, foreigners. Every State “attaches certain rights and obligations” to the status of citizenship, this is intended to create internal inclusivity as to exclude “persons who belong to other States.”120 There is a conceptually clear, “legally consequential, and ideologically charged distinction between citizens and foreigners.”121 The State claims to be the State of, and for, “a particular, bounded citizenry; it claims legitimacy by claiming to express the will and further the interests of that [of] citizenry.”122

Sociology has tended to take the “existence of a bounded national ‘society’ for granted and to focus 112 Brittany Carter, supra note 111.

113 Id. at 6.

114 Ibid.

115 Rogers Brubaker, 108.

116 Ibid.

117 John Clark, et all, 34.

118 Ibid.

119 Rogers Brubaker, 110.

120 Ibid.

121 Ibid.

122 Ibid.

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on institutions and processes internal to that society.”123 Despite there being an emerging research tradition of “world-system analysis,” this has tended to focus on the political economy, neglecting, specifically, social and political structures.124 The expression of citizenship as a site of socio-historical relevance can help us critically engage with various problems associated with formal citizenship and the nation-state, such as the political contingency of statelessness in relation to the existence of the State. For citizenship is not simply a “legal formula,” it is an increasingly salient social and cultural fact.125 As a powerful instrument of social closure,” citizenship occupies a central place in the administrative structure and political culture” of the modern nation-state and State system.126

Anti-Blackness from which Citizenship Derives

In analyzing the ideological state apparatus denoted by the institution of law, the Black body, existence, and experience as sites from which social order derives is particularly useful. Especially with regards to Black citizenship, which has evolved from its intentional exclusionary origins with, reference to the general concept of citizenship, to a more provisional one since the late nineteenth century. In an effort to synthesize notions of belonging, it is imperative to critically consider from what does even the simplest of terms get its meaning. This will typically necessitate an existence of something it could never mean.

For example, Blackness exists in opposition to whiteness, and as we have evolved from racial dichotomies, it is still important that we situate ourselves in the origins of racial articulation, as we will find that the racial dichotomy is one of the most useful tools in understanding how deeply embedded the politics of identity and otherness are into our social systems. This becomes more apparent when we understand race and anti-Blackness as a spectrum that is experienced in various degrees depending on how close in proximity one is to either Black or white. When we realize that Black will always be situated in contrariety to white and will never be or have access to whiteness, otherwise these words would have no meaning and Blackness as we know it would seize to exist, the implications of how the colonial world has shaped our contemporary understandings and usage of concepts like citizenship is crucial to comprehending the intended functionality and consequences of an inherently exclusionary concept. Anti-colonial and postcolonial thought that engages the Black existence in more formative ways, rather than a perpetual state of victimhood, come to understand that race and land are integral parts in theorization.

The social and political realities of Blackness cannot be ignored when it comes to exploring both lived and inherited experiences of oppressions. For it is not the “colonized, the oppressed, the Indigenous, the Black” who places themselves in historical moments of disenfranchisement, it is the society that instinctually recreates the same systems of disenfranchisement in covert ways that places the Black existence in the immortal socio-historical position of other. When the anti- or even post-colonial intellectual writes and speaks about “otherness and alterity,” this is a gesture to a stagnant status of objective being, as opposed to an active space to acknowledge that knowledge and experience reside “in bodies and cultural memories,” thus adding valuable complexity to the other.

Narrating and focusing on lived experiences of Black lives that is often delineated through various 123 Rogers Brubaker, supra note 122, at 112.

124 Id. at 113.

125 John Clark, et all, 36 126 George J. Sefa Dei, 121

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social policies, starting with early markers of nationality law, as well as Black identities as historical arcs is about theorizing social existence. Anti-colonial subversion or “disruption of Whiteness,” is not merely an obsession with whiteness and the race/pigmentation discourse. It is a realization that the body and existence of the other is political, consequential, and meaningful even in a white supremacist state that asserts otherwise. History has become both a tool and a weapon of colonization, a reality we must counter by situating the socio-historical realities of colonialism and racism in theorizing how our social systems have come to exist as derivatives and anti-Blackness.

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